feat: v9.0.0 — three new agent templates (Discovery, Stakeholder Comms, Launch)
This release adds three new agent templates to the library, bringing the total to four. New templates: - PM Discovery Agent: synthesises customer interviews from Notion or Google Drive, identifies cross-interview themes, scores assumption confidence, generates follow-up questions - PM Stakeholder Comms Agent: detects audience type (executive/investor/stakeholder/board), pulls activity from Linear/Jira/Drive, drafts in audience-appropriate format - PM Launch Agent: end-to-end launch coordination with channel-specific content, calendar, success metrics, and launch checklist Each template follows the established pattern: README, AGENT.md, orchestrate.sh, 2 subagents, connectors with example configs, examples, smoke test. Total file count: 37 new files across 3 templates. Updated README to position library as 4-template collection. Bumped marketplace.json from v8.0.0 to v9.0.0.
This commit is contained in:
mohitagw15856
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---
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name: pm-discovery-agent
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version: 1.0.0
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description: "End-to-end customer discovery synthesis agent. Reads interview notes from Notion or Google Drive, synthesises themes across interviews, scores assumption confidence, and produces a structured discovery report. Use when synthesising user research, preparing discovery readouts, or extracting actionable insights from a batch of customer interviews."
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author: Mohit Aggarwal
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license: MIT
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---
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# PM Discovery Agent
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## Configuration
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Update these defaults to match your team. Override at runtime via `orchestrate.sh` flags.
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```yaml
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discovery_defaults:
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interview_count: 8 # how many interviews to include in synthesis
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include_low_confidence: true # show low-confidence findings (with explicit flagging)
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flag_threshold_interviews: 5 # warn if running on fewer interviews than this
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sources:
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primary_source: notion # notion | google-drive
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notion_settings:
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sort_by: last_modified
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filter_property: status
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filter_value: completed
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google_drive_settings:
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file_type: google_doc # only process Google Docs in the folder
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sort_by: modified_time
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output:
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format: markdown
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include_raw_quotes: true # include verbatim quotes in the report
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include_follow_up_questions: true
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output_directory: ./output
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```
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---
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## Agent system prompt
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You are the PM Discovery Agent. Your role is to take a batch of customer interview notes and a research question, then produce a synthesis report a PM can actually act on.
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You operate in this order:
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1. **Pull interview notes** from the configured source (Notion database or Google Drive folder). Filter by:
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- Most recently completed interviews
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- Interviews tagged with the relevant project or research scope
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- The configured interview count (default 8)
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2. **Verify input quality.** Before synthesis, check:
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- At least 5 interviews are available (warn if fewer)
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- Each interview has substantive notes (warn about thin notes)
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- Notes are recent (warn if any are >90 days old, as context may have changed)
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3. **Call the Theme Synthesiser subagent** to identify patterns across interviews. Provide it: the full text of all interviews, the research question, and any segment filters. It returns a list of themes with supporting evidence.
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4. **Use the `job-story-mapper` skill** to convert key themes into structured job stories. Provide it: the themes from step 3 and the research question. It produces job stories in "When [situation], I want to [motivation], so I can [expected outcome]" format.
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5. **Call the Assumption Scorer subagent** to score confidence for each finding. Provide it: themes, job stories, and the underlying interview evidence. It returns each finding with: confidence level (high/medium/low), supporting interview count, contradicting evidence (if any), and validation status.
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6. **Use the `user-interview-synthesis` skill** to draft the final discovery report. Provide it: research question, themes, job stories, confidence scores. It produces a structured report.
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7. **Identify follow-up questions** for the next round of interviews based on:
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- Findings flagged as low confidence (need more evidence)
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- Themes mentioned by only 1-2 interviewees (could be signal or noise)
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- Contradictions between interviews (need clarification)
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- Areas the original research question didn't fully cover
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8. **Combine outputs** into a single discovery report with these sections:
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- Research Question and Methodology
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- Executive Summary (top 3-5 findings)
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- Themes (sorted by confidence)
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- Job Stories
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- Confidence Assessment per Finding
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- Verbatim Quotes (most representative)
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- Follow-up Questions for Next Round
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- Appendix: Interview Summary
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9. **Save** to the configured output directory.
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---
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## Quality checks before returning output
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Before returning the final output, verify:
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- [ ] Every theme references at least one specific interview as evidence
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- [ ] Every job story has the full "When/I want to/So I can" structure
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- [ ] Every finding has an explicit confidence level (no findings without scoring)
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- [ ] Verbatim quotes are exact (not paraphrased or "cleaned up")
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- [ ] Follow-up questions are specific (not generic "tell me more")
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- [ ] Low-confidence findings are explicitly flagged in the report (not buried)
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- [ ] Contradictions between interviews are surfaced, not silently smoothed over
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- [ ] Output file is saved to the configured directory
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---
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## Tools required
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| Tool | Purpose |
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|---|---|
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| notion-connector / google-drive-connector | Pull interview notes |
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| theme-synthesiser (subagent) | Identify cross-interview themes |
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| assumption-scorer (subagent) | Score confidence for findings |
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| user-interview-synthesis (skill) | Draft final discovery report |
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| job-story-mapper (skill) | Convert themes into JTBD format |
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| filesystem-write | Save output document |
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---
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## When to invoke this agent
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Use this agent when:
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- You've completed a batch of customer interviews and need to synthesise them
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- Preparing a discovery readout for stakeholders
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- Closing out a research sprint or quarter
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- Validating or invalidating a product hypothesis with user research
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Do NOT use this agent for:
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- Single interview summaries (use the `user-interview-synthesis` skill directly)
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- Planning interviews (use the `discovery-interview-guide` skill)
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- Pure quantitative research (this is for qualitative interviews)
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- Real-time interview transcription (use a dedicated tool like Otter or Granola)
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---
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## Example invocation
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```bash
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bash orchestrate.sh \
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--research-question "Why are users abandoning the onboarding flow?" \
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--interview-source notion \
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--interview-count 10
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```
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See `examples/output-example.md` for what the output looks like.
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---
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## Architecture notes
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This agent template demonstrates the three-component pattern from Anthropic's May 2026 agent templates announcement:
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- **Skills** (`user-interview-synthesis`, `job-story-mapper`, `discovery-interview-guide`, `assumption-mapper`) — provide structured output formats. Reused from the main pm-claude-skills library.
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- **Connectors** (`notion`, `google-drive`) — provide governed data access. Configured separately so credentials don't live in prompts.
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- **Subagents** (`theme-synthesiser`, `assumption-scorer`) — provide focused analytical capabilities specific to discovery synthesis.
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The orchestration script wires these together. The system prompt above tells Claude how to use them in sequence.
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@@ -0,0 +1,211 @@
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# PM Discovery Agent — Agent Template
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> **An end-to-end customer discovery agent. Reads interview notes from Notion or Google Drive, synthesises themes, scores assumption confidence, and produces a structured discovery report a PM can actually act on.**
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This is the second agent template in the pm-claude-skills library. Like the [PM Sprint Agent](../pm-sprint-agent/), it follows the architecture Anthropic introduced for [financial services agent templates](https://www.anthropic.com/news/finance-agents) on May 5, 2026 — packaging **skills + connectors + subagents** into a single runnable workflow.
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---
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## What it does
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You point this agent at a folder of customer interview notes or transcripts. It does the rest:
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1. **Pulls interview notes** from Notion (a database) or Google Drive (a folder)
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2. **Synthesises themes** across all interviews using the Theme Synthesiser subagent
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3. **Maps insights to job stories** using the `job-story-mapper` skill
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4. **Scores assumption confidence** for each finding using the Assumption Scorer subagent
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5. **Drafts the discovery report** using the `user-interview-synthesis` skill
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6. **Identifies follow-up questions** for the next round of interviews
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7. **Saves the report** as a structured markdown document
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End-to-end: roughly 3-5 minutes for 8-12 interview transcripts. The manual version of this synthesis takes most PMs a full day — and the inconsistency is the bigger problem than the time.
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---
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## Why this matters
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Customer discovery is the workflow PMs say they care about most and consistently underinvest in. The reasons are predictable: synthesis is hard, themes are easy to over-interpret, confirmation bias is real, and writing it up takes hours. So PMs do interviews, take notes, and never come back to them properly.
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This agent doesn't replace the discovery work. It removes the synthesis bottleneck so the discovery work actually pays off.
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---
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## What's inside this template
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```
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templates/pm-discovery-agent/
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├── README.md ← you are here
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├── AGENT.md ← agent definition (system prompt + tool list)
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├── orchestrate.sh ← orchestration script
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├── skills/ ← skills used by this agent
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│ ├── README.md
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│ ├── discovery-interview-guide/SKILL.md ← (symlink)
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│ ├── user-interview-synthesis/SKILL.md ← (symlink)
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│ ├── job-story-mapper/SKILL.md ← (symlink)
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│ └── assumption-mapper/SKILL.md ← (symlink)
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├── subagents/
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│ ├── theme-synthesiser.md ← cross-interview theme detection
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│ └── assumption-scorer.md ← confidence scoring for findings
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├── connectors/
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│ ├── README.md ← connector setup guide
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│ ├── notion.example.json ← Notion database connector
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│ └── google-drive.example.json ← Google Drive folder connector
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├── examples/
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│ ├── input-example.md ← what you feed the agent
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│ ├── output-example.md ← what the agent produces
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│ └── sample-interview.md ← example interview note format
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└── tests/
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└── smoke-test.md ← manual smoke test for new installations
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```
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---
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## Quick install (5 minutes)
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### Prerequisites
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- Claude Code installed
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- The full skills library installed: `/plugin marketplace add mohitagw15856/pm-claude-skills`
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- Either a Notion workspace or Google Drive (most PMs have both)
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### Setup
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**Choose your input source.** PMs typically store interview notes in one of two places:
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- **Notion** — if you keep interviews in a Notion database (most common for PMs at scaleups)
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- **Google Drive** — if you keep interviews as Google Docs in a folder (most common for PMs at startups and large enterprises)
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Set up the connector for whichever one you use. You don't need both.
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### Notion setup (5 minutes)
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```bash
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cd templates/pm-discovery-agent/connectors
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cp notion.example.json notion.json
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# Edit notion.json with your database_id and page properties
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```
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Detailed setup steps in `connectors/README.md`.
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### Google Drive setup (5 minutes)
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```bash
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cd templates/pm-discovery-agent/connectors
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cp google-drive.example.json google-drive.json
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# Edit with your folder_id and authentication details
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```
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### Test the smoke test
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```bash
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cd templates/pm-discovery-agent
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bash orchestrate.sh --research-question "Test discovery synthesis" --dry-run
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```
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If the dry-run completes without errors, you're ready to run a real discovery synthesis.
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---
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## Running the agent
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### Standard usage
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```bash
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bash orchestrate.sh \
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--research-question "Why are users abandoning the onboarding flow?" \
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--interview-source notion \
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--interview-count 10
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```
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The agent will:
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1. Pull the latest 10 interview notes from your configured Notion database
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2. Run the Theme Synthesiser subagent to identify patterns across interviews
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3. Run the `job-story-mapper` skill to convert findings into structured job stories
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4. Run the Assumption Scorer subagent to flag which findings are high vs low confidence
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5. Run the `user-interview-synthesis` skill to draft the final report
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6. Identify follow-up questions for the next round of interviews
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7. Save the report to `output/discovery-[date].md`
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### Configuration options
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| Flag | Required | Default | Description |
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|---|---|---|---|
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| `--research-question` | Yes | — | The question your discovery is trying to answer |
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| `--interview-source` | Yes | — | `notion` or `google-drive` |
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| `--interview-count` | No | 8 | How many interviews to include in synthesis |
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| `--filter-by-segment` | No | — | If your notes are tagged by segment, filter to one (e.g., "enterprise") |
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| `--include-low-confidence` | No | true | Include low-confidence findings in the report (with explicit flagging) |
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| `--dry-run` | No | false | Validate config without running the workflow |
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---
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## How interview notes should be structured
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The agent works best when interview notes follow a consistent structure. There's no rigid format required, but the more your notes contain, the better the synthesis.
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**Minimum requirements** (the agent will work with any notes that have these):
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- Interviewee identifier (name, role, or anonymous ID)
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- Date of interview
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- Free-text notes or transcript
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**Recommended additions** (for better synthesis):
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- Segment or persona tags
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- Key quotes pulled out
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- Initial interpretations or hypotheses
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- Follow-up questions noted
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See `examples/sample-interview.md` for a template you can use to standardise your team's interview notes.
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---
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## Why this architecture
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The template follows the same three-component pattern as PM Sprint Agent:
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**Skills** provide the structured output formats. The `user-interview-synthesis` skill knows what a good discovery report contains. The `job-story-mapper` knows the JTBD format. The `assumption-mapper` knows how to structure assumptions. These already exist in this library — the agent doesn't reinvent them.
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**Connectors** provide governed access to data. Notion and Google Drive are where PMs actually keep interview notes. Credentials live in environment variables, never in prompts.
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**Subagents** handle specialised analysis. Theme synthesis across 10 interviews requires holding 10 documents in mind and finding patterns — that's a focused job for a subagent with a specific system prompt. Confidence scoring requires distinguishing "5 people said this" from "1 person said this dramatically" — also a focused job for a subagent.
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---
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## Customisation
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### Adapt to your team's discovery process
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The default agent uses the generic discovery skills from the main library. If your team has specific conventions — particular persona definitions, opportunity scoring frameworks, ICE prioritisation for follow-ups — fork the relevant skill into `skills/` and modify it. The orchestrate script will pick up the local version.
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### Add additional analysis steps
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If your discovery process includes things this template doesn't cover — competitive mention extraction, willingness-to-pay analysis, feature request triage — add subagents in `subagents/` for those analyses and update `orchestrate.sh` to call them.
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### Switch interview sources
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If you use a tool other than Notion or Google Drive — Dovetail, Granola, Otter, Reflect, Roam, Coda — you can build a connector following the pattern in `connectors/README.md`. PRs welcome for additional connectors.
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---
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## Limitations and honest caveats
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**The synthesis is only as good as the notes.** If your interview notes are sparse, generic, or inconsistent in format, the synthesis will reflect that. Spending 15 minutes after each interview to write proper notes pays off enormously when you run the agent.
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**Theme synthesis can over-cluster.** The Theme Synthesiser will find patterns even in small datasets. If you're running it on 3 interviews, treat the themes as hypotheses to validate, not conclusions. The agent flags this when interview count is low.
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**Confidence scoring is heuristic, not statistical.** The Assumption Scorer uses simple rules — how many people mentioned it, how strongly, how recently. It's not running statistical analysis. Use the scores as a directional ranking, not a precise measurement.
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**No autonomous execution.** This template runs as a Claude Code plugin — it produces outputs for human review, it doesn't autonomously create JIRA tickets or modify your discovery database. For autonomous execution, deploy via Claude Managed Agents using the same skills, connectors, and subagent definitions.
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---
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## Where to learn more
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- [Anthropic's announcement of agent templates](https://www.anthropic.com/news/finance-agents) (May 2026)
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- [The PM Sprint Agent template](../pm-sprint-agent/) (first template in this library)
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- [The pm-claude-skills main README](../../README.md)
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- [Part 17 article — Building the PM Discovery Agent](#) *(link added when published)*
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---
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*Built and maintained by [Mohit Aggarwal](https://medium.com/@mohit15856) | Second agent template in [pm-claude-skills](https://github.com/mohitagw15856/pm-claude-skills)*
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@@ -0,0 +1,169 @@
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# Connectors — PM Discovery Agent
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This folder contains the connector configurations for the PM Discovery Agent. You only need to set up the connector for whichever tool your team uses for interview notes — Notion or Google Drive.
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## Which connector should I use?
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| If your interview notes live in... | Use this connector |
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|---|---|
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| A Notion database | `notion.json` |
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| A Google Drive folder of Google Docs | `google-drive.json` |
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| Both | Pick the one with more interviews — agents work better with more data |
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| Somewhere else (Dovetail, Granola, Otter, etc.) | See "Building a connector for another system" below |
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## Notion setup (5 minutes)
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This is the fastest path if you keep interviews in Notion.
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### 1. Create a Notion integration
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- Go to https://www.notion.so/my-integrations
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- Click "+ New integration"
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- Name it "PM Discovery Agent"
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- Leave defaults
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- Click Submit
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- Copy the "Internal Integration Token" (starts with `secret_`)
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### 2. Set the environment variable
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```bash
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export NOTION_INTEGRATION_TOKEN='secret_xxxxxxxxxxxxxxxxxxxxxxxx'
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```
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To make permanent, add to `~/.zshrc` or `~/.bashrc`.
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### 3. Share your interview database with the integration
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- Open your interview notes database in Notion
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- Click the `...` menu in the top right
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- Select "Add connections"
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- Choose "PM Discovery Agent"
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The integration now has access to that database.
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### 4. Find your database ID
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The database ID is in the URL when viewing the database. Format: `notion.so/your-workspace/DATABASE_ID?v=...`
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The ID is the long string between `/` and `?`. Copy it.
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### 5. Configure the connector
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```bash
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cp notion.example.json notion.json
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```
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Open `notion.json` and update:
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- `database_id` — paste the ID from step 4
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- `expected_properties` — adjust to match your actual property names (the defaults assume Name, Interview Date, Interviewee, Segment, Status, Tags)
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### 6. Test
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```bash
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cd ../ # back to pm-discovery-agent root
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bash orchestrate.sh --research-question "Test" --interview-source notion --dry-run
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```
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If you see "✓ Dry-run complete", you're set up.
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## Google Drive setup (10 minutes)
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|
||||
A bit more setup than Notion, but works well if your team uses Google Docs for interviews.
|
||||
|
||||
### 1. Create a Google Cloud project
|
||||
|
||||
- Go to https://console.cloud.google.com/
|
||||
- Click "Select a project" > "New Project"
|
||||
- Name it "PM Discovery Agent"
|
||||
- Click Create
|
||||
|
||||
### 2. Enable the APIs
|
||||
|
||||
- In the project, search for "Google Drive API" in the API library
|
||||
- Click Enable
|
||||
- Search for "Google Docs API"
|
||||
- Click Enable
|
||||
|
||||
### 3. Create a service account
|
||||
|
||||
- Go to IAM & Admin > Service Accounts
|
||||
- Click "+ Create Service Account"
|
||||
- Name: "pm-discovery-reader"
|
||||
- Description: "Read-only access for PM Discovery Agent"
|
||||
- Click Create
|
||||
- Skip the optional permissions step
|
||||
- Click Done
|
||||
|
||||
### 4. Download the service account key
|
||||
|
||||
- Click on the service account you just created
|
||||
- Go to the "Keys" tab
|
||||
- Click "Add Key" > "Create new key"
|
||||
- Choose JSON
|
||||
- Save the file somewhere secure (e.g., `~/.config/pm-discovery-agent/service-account.json`)
|
||||
|
||||
### 5. Set the environment variable
|
||||
|
||||
```bash
|
||||
export GOOGLE_APPLICATION_CREDENTIALS='/Users/yourname/.config/pm-discovery-agent/service-account.json'
|
||||
```
|
||||
|
||||
To make permanent, add to `~/.zshrc` or `~/.bashrc`.
|
||||
|
||||
### 6. Share your interview folder with the service account
|
||||
|
||||
- Find the service account email (it looks like `pm-discovery-reader@your-project.iam.gserviceaccount.com`)
|
||||
- Open your interview notes folder in Google Drive
|
||||
- Click Share
|
||||
- Paste the service account email
|
||||
- Set permission to Viewer
|
||||
- Click Send
|
||||
|
||||
### 7. Find your folder ID
|
||||
|
||||
Open the folder in Google Drive. The URL looks like: `drive.google.com/drive/folders/FOLDER_ID_HERE`
|
||||
|
||||
Copy the ID after `/folders/`.
|
||||
|
||||
### 8. Configure the connector
|
||||
|
||||
```bash
|
||||
cp google-drive.example.json google-drive.json
|
||||
```
|
||||
|
||||
Open `google-drive.json` and update:
|
||||
- `folder_id` — paste the ID from step 7
|
||||
|
||||
### 9. Test
|
||||
|
||||
```bash
|
||||
cd ../ # back to pm-discovery-agent root
|
||||
bash orchestrate.sh --research-question "Test" --interview-source google-drive --dry-run
|
||||
```
|
||||
|
||||
## Building a connector for another system
|
||||
|
||||
If your interview notes live somewhere other than Notion or Google Drive, you can build a connector following the same pattern. Common alternatives PMs use:
|
||||
|
||||
- **Dovetail** — has a research API; build a connector for the analysis endpoint
|
||||
- **Granola / Otter / Fathom** — meeting recorders; build a connector that pulls transcripts
|
||||
- **Reflect / Roam / Logseq** — personal note-taking apps; build a connector for the markdown files
|
||||
- **Coda / Airtable** — alternative databases; build a connector for the rows API
|
||||
- **Local files** — markdown files in a folder; build a simple file-reading connector
|
||||
|
||||
A connector needs three things:
|
||||
1. A configuration file defining the data source URL, credentials, and available operations
|
||||
2. An API client the orchestration script can call
|
||||
3. A mapping from the source's data model to what the agent expects (interview ID, date, interviewee, content, tags)
|
||||
|
||||
Copy `notion.example.json` or `google-drive.example.json` as a starting point.
|
||||
|
||||
If you build a connector for a new system, consider raising a PR back to the main pm-claude-skills repo.
|
||||
|
||||
## Security notes
|
||||
|
||||
**Credentials live in environment variables, not in the JSON files.** This means you can commit your `notion.json` or `google-drive.json` to source control without leaking credentials.
|
||||
|
||||
**Use read-only access where possible.** The agent only needs to read interview notes — never to modify them. Both Notion integrations and Google Drive service accounts can be set up with read-only permissions. Use them.
|
||||
|
||||
**Rotate credentials periodically.** Both Notion integration tokens and Google service account keys can be regenerated. Do this every 90 days as a security practice.
|
||||
@@ -0,0 +1,86 @@
|
||||
{
|
||||
"connector_name": "google-drive",
|
||||
"version": "1.0.0",
|
||||
"description": "Google Drive connector for the PM Discovery Agent. Reads interview notes from a Google Drive folder where each interview is a Google Doc.",
|
||||
|
||||
"configuration": {
|
||||
"folder_id": "FOLDER_ID_HERE",
|
||||
"file_type": "application/vnd.google-apps.document",
|
||||
"include_subfolders": false,
|
||||
"expected_naming_convention": "YYYY-MM-DD - Interviewee Name.gdoc",
|
||||
"default_sort": {
|
||||
"field": "modifiedTime",
|
||||
"direction": "desc"
|
||||
},
|
||||
"default_filters": {
|
||||
"exclude_trashed": true,
|
||||
"min_word_count": 100
|
||||
},
|
||||
"rate_limit_requests_per_minute": 60
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"_comment": "Google Drive uses OAuth 2.0. You'll need to create a Google Cloud project and enable the Drive API. Easiest path: use a service account with access to your folder.",
|
||||
"auth_method": "service_account",
|
||||
"service_account_key_path_env_var": "GOOGLE_APPLICATION_CREDENTIALS",
|
||||
"service_account_key_placeholder": "/path/to/service-account-key.json"
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "list_recent_documents",
|
||||
"description": "Get the N most recent Google Docs in the configured folder",
|
||||
"filters": ["modifiedAfter", "name_contains", "starred"],
|
||||
"max_results": 50
|
||||
},
|
||||
{
|
||||
"name": "get_document_content",
|
||||
"description": "Fetch the full text content of a specific Google Doc",
|
||||
"required_input": "file_id"
|
||||
},
|
||||
{
|
||||
"name": "search_documents",
|
||||
"description": "Search document content by keyword across the folder",
|
||||
"required_input": "search_query"
|
||||
}
|
||||
],
|
||||
|
||||
"permissions_required": [
|
||||
"https://www.googleapis.com/auth/drive.readonly",
|
||||
"https://www.googleapis.com/auth/documents.readonly"
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Go to Google Cloud Console: https://console.cloud.google.com/",
|
||||
"2. Create a new project (or use existing) — name it something like 'PM Discovery Agent'",
|
||||
"3. Enable the Google Drive API and Google Docs API for the project",
|
||||
"4. Create a service account: IAM & Admin > Service Accounts > Create Service Account",
|
||||
"5. Download the service account key as JSON",
|
||||
"6. Save the JSON file to a secure location (e.g., ~/.config/pm-discovery-agent/service-account.json)",
|
||||
"7. Set the environment variable: export GOOGLE_APPLICATION_CREDENTIALS='/path/to/service-account.json'",
|
||||
"8. Find the folder ID where your interview notes live: open the folder in Google Drive, the ID is in the URL (drive.google.com/drive/folders/FOLDER_ID_HERE)",
|
||||
"9. Share that folder with the service account email (it looks like xxx@your-project.iam.gserviceaccount.com) — give it Viewer access",
|
||||
"10. Update folder_id in this file",
|
||||
"11. Save this file as 'google-drive.json' (without the .example)",
|
||||
"12. Test the connection: bash orchestrate.sh --research-question 'Test' --interview-source google-drive --dry-run"
|
||||
],
|
||||
|
||||
"_alternative_simpler_setup": [
|
||||
"If creating a service account feels heavy, you can use OAuth user credentials instead:",
|
||||
"1. Go to APIs & Services > Credentials in Google Cloud Console",
|
||||
"2. Create OAuth client ID > Desktop application",
|
||||
"3. Download the credentials JSON",
|
||||
"4. The first time the agent runs, it'll open a browser for you to authorise",
|
||||
"This is simpler but requires re-authorisation if the token expires."
|
||||
],
|
||||
|
||||
"_folder_organisation_recommendation": [
|
||||
"If you're starting fresh, organise your interview notes folder like this:",
|
||||
"- One folder for the discovery project",
|
||||
"- One Google Doc per interview, named '2026-05-10 - Sarah Chen.gdoc' (date + interviewee)",
|
||||
"- Inside each doc: structured headers for Background, Notes, Key Quotes, Observations, Follow-ups",
|
||||
"Consistent structure makes the synthesis dramatically better."
|
||||
],
|
||||
|
||||
"_rate_limit_notes": "Google Drive's API rate limits are generous (1000 requests per 100 seconds). The agent uses approximately 12-15 API calls per discovery synthesis."
|
||||
}
|
||||
@@ -0,0 +1,84 @@
|
||||
{
|
||||
"connector_name": "notion",
|
||||
"version": "1.0.0",
|
||||
"description": "Notion connector for the PM Discovery Agent. Reads interview notes from a Notion database where each interview is a database row.",
|
||||
|
||||
"configuration": {
|
||||
"database_id": "DATABASE_ID_HERE",
|
||||
"workspace_url": "https://www.notion.so/your-workspace",
|
||||
"expected_properties": {
|
||||
"title_property": "Name",
|
||||
"date_property": "Interview Date",
|
||||
"interviewee_property": "Interviewee",
|
||||
"segment_property": "Segment",
|
||||
"status_property": "Status",
|
||||
"tags_property": "Tags"
|
||||
},
|
||||
"default_filters": {
|
||||
"status_is": "Completed",
|
||||
"exclude_archived": true
|
||||
},
|
||||
"default_sort": {
|
||||
"property": "Interview Date",
|
||||
"direction": "descending"
|
||||
},
|
||||
"rate_limit_requests_per_second": 3
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"_comment": "Notion uses an integration token. Create one at https://www.notion.so/my-integrations and share your database with it.",
|
||||
"integration_token_env_var": "NOTION_INTEGRATION_TOKEN",
|
||||
"integration_token_placeholder": "secret_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "list_recent_interviews",
|
||||
"description": "Get the N most recent interviews from the configured database",
|
||||
"filters": ["segment", "tags", "date_range", "status"],
|
||||
"max_results": 50
|
||||
},
|
||||
{
|
||||
"name": "get_interview_content",
|
||||
"description": "Fetch the full page content of a specific interview (notes, transcript, observations)",
|
||||
"required_input": "page_id"
|
||||
},
|
||||
{
|
||||
"name": "search_interviews",
|
||||
"description": "Search interview content by keyword",
|
||||
"required_input": "search_query"
|
||||
}
|
||||
],
|
||||
|
||||
"permissions_required": [
|
||||
"Read content",
|
||||
"Read user information without email"
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Create a Notion integration at https://www.notion.so/my-integrations",
|
||||
"2. Click '+ New integration', name it 'PM Discovery Agent', leave defaults",
|
||||
"3. After creation, copy the Internal Integration Token (starts with 'secret_')",
|
||||
"4. Set the environment variable: export NOTION_INTEGRATION_TOKEN='secret_xxxxx...'",
|
||||
"5. Open your interview notes database in Notion",
|
||||
"6. Click '...' menu in top right > 'Add connections' > select your new integration",
|
||||
"7. Find your database ID: it's the long string in the URL when viewing the database (after the workspace name and before the '?'). Example: notion.so/workspace/abc123def456 — abc123def456 is the ID",
|
||||
"8. Update database_id in this file",
|
||||
"9. Update expected_properties to match your actual property names (the agent expects fields named Name, Interview Date, Interviewee, Segment, Status, Tags — adjust if yours are different)",
|
||||
"10. Save this file as 'notion.json' (without the .example)",
|
||||
"11. Test the connection: bash orchestrate.sh --research-question 'Test' --interview-source notion --dry-run"
|
||||
],
|
||||
|
||||
"_notion_database_setup_recommendation": [
|
||||
"If you don't have a Notion database for interviews yet, create one with these properties:",
|
||||
"- Name (title) — interview identifier or interviewee name",
|
||||
"- Interview Date (date) — when the interview happened",
|
||||
"- Interviewee (text) — who was interviewed",
|
||||
"- Segment (select) — which user segment they belong to",
|
||||
"- Status (select) — Scheduled / Completed / Cancelled",
|
||||
"- Tags (multi-select) — research project, persona, or feature area",
|
||||
"Then write your interview notes in the page body."
|
||||
],
|
||||
|
||||
"_rate_limit_notes": "Notion's API is rate limited to 3 requests per second per integration. The agent typically uses 10-25 API calls per discovery synthesis (depending on interview count), well within rate limits."
|
||||
}
|
||||
@@ -0,0 +1,87 @@
|
||||
# Example: Input to the PM Discovery Agent
|
||||
|
||||
## Command-line invocation
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--research-question "Why are users abandoning the onboarding flow?" \
|
||||
--interview-source notion \
|
||||
--interview-count 10 \
|
||||
--filter-by-segment "smb"
|
||||
```
|
||||
|
||||
## What the agent reads from your connector
|
||||
|
||||
### From Notion
|
||||
|
||||
The agent automatically pulls from your configured Notion database:
|
||||
|
||||
- Most recent N interviews where Status = "Completed"
|
||||
- For each interview:
|
||||
- Title (interviewee name or identifier)
|
||||
- Interview date
|
||||
- Interviewee role and segment tags
|
||||
- Full page content (notes, transcript, observations, quotes)
|
||||
|
||||
If you've applied a segment filter, only interviews matching that segment are included.
|
||||
|
||||
### From Google Drive
|
||||
|
||||
The agent automatically pulls from your configured folder:
|
||||
|
||||
- Most recently modified Google Docs in the folder
|
||||
- For each doc:
|
||||
- Document title
|
||||
- Last modified date
|
||||
- Full text content
|
||||
|
||||
If your filenames follow the `YYYY-MM-DD - Name.gdoc` convention, the agent uses the date for sorting and the name for interviewee identification.
|
||||
|
||||
## What the agent does NOT need from you
|
||||
|
||||
- A summary of what the interviews said — that's what the agent produces
|
||||
- Pre-tagged themes — the agent finds them
|
||||
- A list of which interviews are most important — the agent uses all included interviews
|
||||
- Statistical analysis — this is qualitative discovery, not quantitative
|
||||
|
||||
## What you should know before running
|
||||
|
||||
- **Have at least 5 interviews completed.** The agent works best with 5+ interviews. With fewer, themes will be tagged as "Emerging" rather than "Strong" — directional insights only.
|
||||
- **Have a specific research question.** Vague questions produce vague synthesis. "What do users think?" is too broad. "Why are users abandoning the onboarding flow at step 3?" is specific enough to drive useful synthesis.
|
||||
- **Check your interview notes are accessible.** The agent can only read what your connector has access to. If notes are in a different database/folder than configured, results will be empty.
|
||||
|
||||
## Example: Real-world invocations
|
||||
|
||||
```bash
|
||||
# Standard discovery synthesis from Notion
|
||||
bash orchestrate.sh \
|
||||
--research-question "What's blocking users from completing checkout?" \
|
||||
--interview-source notion \
|
||||
--interview-count 8
|
||||
|
||||
# Synthesis filtered to a specific segment
|
||||
bash orchestrate.sh \
|
||||
--research-question "How are enterprise customers using the API?" \
|
||||
--interview-source notion \
|
||||
--interview-count 12 \
|
||||
--filter-by-segment "enterprise"
|
||||
|
||||
# Synthesis from Google Drive folder (all recent interviews)
|
||||
bash orchestrate.sh \
|
||||
--research-question "What workflows do power users have that we don't support?" \
|
||||
--interview-source google-drive \
|
||||
--interview-count 10
|
||||
|
||||
# Smaller batch with low-confidence findings excluded (cleaner stakeholder report)
|
||||
bash orchestrate.sh \
|
||||
--research-question "Validate our pricing hypothesis" \
|
||||
--interview-source notion \
|
||||
--interview-count 6 \
|
||||
--include-low-confidence false
|
||||
|
||||
# Dry run to validate config
|
||||
bash orchestrate.sh \
|
||||
--research-question "Test" \
|
||||
--interview-source notion \
|
||||
--dry-run
|
||||
```
|
||||
@@ -0,0 +1,176 @@
|
||||
# Discovery Report — May 2026
|
||||
|
||||
**Research Question:** Why are users abandoning the onboarding flow?
|
||||
**Interview Source:** notion
|
||||
**Interview Count:** 10
|
||||
**Generated:** 2026-05-06 14:30 BST
|
||||
|
||||
---
|
||||
|
||||
## Executive Summary
|
||||
|
||||
Across 10 SMB customer interviews, three high-confidence findings emerged about onboarding abandonment:
|
||||
|
||||
1. **Users feel they're being asked to commit before understanding what they're getting.** The current flow asks for credit card details and integration setup before showing any value. 8 of 10 interviews mentioned this directly.
|
||||
|
||||
2. **The integration setup step is the highest-friction point.** Users are willing to set up integrations once they're convinced of value — but doing it before that point feels like extra work for no clear payoff. 7 of 10 interviews mentioned this.
|
||||
|
||||
3. **The pricing display creates anxiety, not clarity.** Showing pricing tiers without clear differentiation between them creates decision paralysis. 6 of 10 interviews described this.
|
||||
|
||||
Two medium-confidence findings worth validating in the next research round:
|
||||
- Users may be abandoning because they confuse onboarding with set-up (5 interviews)
|
||||
- The "skip for now" option may be reducing completion rather than helping (4 interviews)
|
||||
|
||||
---
|
||||
|
||||
## Themes Identified
|
||||
|
||||
### Theme 1: Premature commitment ask (Strong)
|
||||
|
||||
Users feel they're being asked to commit (credit card, integrations, team invites) before they understand what they're getting from the product.
|
||||
|
||||
- **Supporting interviews:** 8 — IDs: I-103, I-105, I-107, I-109, I-110, I-112, I-114, I-115
|
||||
- **Strength:** Strong
|
||||
- **Quotes:**
|
||||
- "I just wanted to see if this would work for my team. Why am I being asked for my credit card?" — I-105
|
||||
- "It felt like I was already a customer before I'd even decided." — I-110
|
||||
- "The first thing it asked me was to invite my whole team. I haven't even tried it yet." — I-114
|
||||
- **Contradicting evidence:** None
|
||||
- **Why this matters:** This is the strongest signal in the synthesis. The team should consider redesigning the flow so users see value before being asked to commit.
|
||||
|
||||
### Theme 2: Integration setup friction (Strong)
|
||||
|
||||
The integration setup step (connecting to Slack, Google Drive, etc.) is happening too early in the flow. Users are willing to set up integrations once convinced, but doing it before is friction.
|
||||
|
||||
- **Supporting interviews:** 7 — IDs: I-103, I-105, I-109, I-110, I-112, I-114, I-115
|
||||
- **Strength:** Strong
|
||||
- **Quotes:**
|
||||
- "I gave up at the Slack integration step. I wasn't sure I wanted my team to know I was trying this yet." — I-109
|
||||
- "Why does it need access to my Google Drive before I've even seen what it does?" — I-103
|
||||
- **Contradicting evidence:** I-107 mentioned that integration setup felt natural — "I expected to connect my tools, that's normal." This is a single contradiction within the broader pattern.
|
||||
- **Why this matters:** This connects to Theme 1. Users want value first, commitment second.
|
||||
|
||||
### Theme 3: Pricing display causes anxiety (Strong)
|
||||
|
||||
Showing all three pricing tiers during onboarding creates decision paralysis rather than clarity. Users aren't sure which tier they need.
|
||||
|
||||
- **Supporting interviews:** 6 — IDs: I-105, I-107, I-110, I-112, I-114, I-115
|
||||
- **Strength:** Strong
|
||||
- **Quotes:**
|
||||
- "I don't know if I'm a Pro user or a Team user. I just wanted to try it." — I-107
|
||||
- "Showing me three columns of features I don't understand made me close the tab." — I-114
|
||||
- **Contradicting evidence:** None
|
||||
- **Why this matters:** The current pricing display is optimised for users who already know they want to buy. For first-time users, it's a distraction.
|
||||
|
||||
### Theme 4: Onboarding-vs-setup conflation (Moderate)
|
||||
|
||||
Users may not be distinguishing between "onboarding" (learning the product) and "setup" (configuring it for their team). They expected the first to come before the second.
|
||||
|
||||
- **Supporting interviews:** 5 — IDs: I-103, I-109, I-110, I-114, I-115
|
||||
- **Strength:** Moderate
|
||||
- **Quotes:**
|
||||
- "I thought I'd see how to use it. Instead I was configuring it." — I-115
|
||||
- "Onboarding should be 'here's what this does'. Not 'fill out these forms'." — I-103
|
||||
- **Contradicting evidence:** None — but this finding is partially redundant with Theme 1.
|
||||
- **Why this matters:** Could be reframed: the issue isn't onboarding vs. setup specifically — it's that setup is happening before value demonstration.
|
||||
|
||||
### Theme 5: "Skip for now" reduces completion (Emerging)
|
||||
|
||||
The "Skip for now" option offered at several points may be reducing completion rather than helping users. Users who skip rarely come back to complete those steps.
|
||||
|
||||
- **Supporting interviews:** 4 — IDs: I-105, I-110, I-112, I-114
|
||||
- **Strength:** Emerging
|
||||
- **Quotes:**
|
||||
- "I clicked Skip on three things. Then I forgot to come back." — I-110
|
||||
- **Contradicting evidence:** None — but only 4 interviews and behavioural data would validate this better than interview observations.
|
||||
- **Why this matters:** If validated, this suggests the team should either remove the skip option or implement reminders.
|
||||
|
||||
---
|
||||
|
||||
## Job Stories
|
||||
|
||||
### Job Story 1
|
||||
**When** I'm evaluating a new SaaS tool for my team,
|
||||
**I want to** see what it does and how it would feel to use,
|
||||
**So I can** decide whether to invest the time in setting it up properly.
|
||||
|
||||
### Job Story 2
|
||||
**When** I'm in the early evaluation phase of a tool,
|
||||
**I want to** avoid commitments (payment, team invites, integrations),
|
||||
**So I can** stay in low-stakes exploration mode.
|
||||
|
||||
### Job Story 3
|
||||
**When** I'm shown pricing during evaluation,
|
||||
**I want to** understand which tier fits my situation without comparing all features,
|
||||
**So I can** focus on whether the product solves my problem.
|
||||
|
||||
---
|
||||
|
||||
## Confidence Assessment
|
||||
|
||||
| Finding | Confidence | Breadth | Quality | Contradictions |
|
||||
|---|---|---|---|---|
|
||||
| Premature commitment ask | High | 8 interviews | High | None |
|
||||
| Integration setup friction | High | 7 interviews | High | 1 (likely segment-specific) |
|
||||
| Pricing causes anxiety | High | 6 interviews | High | None |
|
||||
| Onboarding/setup conflation | Medium | 5 interviews | Medium | None — but redundant with Theme 1 |
|
||||
| "Skip for now" reduces completion | Low | 4 interviews | Medium | None — needs behavioural data |
|
||||
|
||||
### Recommended actions
|
||||
|
||||
- **High confidence findings:** Safe to use in product decisions. Can frame in stakeholder communications without caveat.
|
||||
- **Medium confidence findings:** Use directionally. Validate with one more interview round before major product decisions.
|
||||
- **Low confidence findings:** Treat as hypothesis. Do not use in product decisions until validated with behavioural analytics.
|
||||
|
||||
---
|
||||
|
||||
## Verbatim Quotes (Most Representative)
|
||||
|
||||
> "I just wanted to see if this would work for my team. Why am I being asked for my credit card?" — I-105
|
||||
|
||||
> "It felt like I was already a customer before I'd even decided." — I-110
|
||||
|
||||
> "The first thing it asked me was to invite my whole team. I haven't even tried it yet." — I-114
|
||||
|
||||
> "I don't know if I'm a Pro user or a Team user. I just wanted to try it." — I-107
|
||||
|
||||
> "Onboarding should be 'here's what this does'. Not 'fill out these forms'." — I-103
|
||||
|
||||
---
|
||||
|
||||
## Follow-up Questions for Next Round
|
||||
|
||||
Based on findings flagged as low or medium confidence, and gaps in the original research question:
|
||||
|
||||
1. **Validate "Skip for now" hypothesis:** Pair the next 5 interviews with behavioural analytics on completion rates for users who skip vs. don't skip. — Would validate Theme 5.
|
||||
|
||||
2. **Test the integration ordering:** What if integration setup came after the first value demonstration? Would users still be reluctant? — Would help design the redesigned flow.
|
||||
|
||||
3. **Probe enterprise users:** All 10 interviews were SMB. Do enterprise users have different expectations about commitment depth during evaluation? — Fills the segment gap.
|
||||
|
||||
4. **Validate the redundancy of Themes 1 and 4:** Are these the same finding stated differently, or genuinely separate? — Affects how we frame the findings to stakeholders.
|
||||
|
||||
5. **Understand competitive context:** Are users abandoning to try competitors, or just not coming back? — Would tell us if this is a problem of conversion specifically or activation more broadly.
|
||||
|
||||
---
|
||||
|
||||
## Appendix: Interview Summary
|
||||
|
||||
| ID | Date | Interviewee | Segment | Notes Length |
|
||||
|---|---|---|---|---|
|
||||
| I-103 | 2026-04-15 | David Park, founder | SMB | Substantial |
|
||||
| I-105 | 2026-04-17 | Sarah Lee, marketing manager | SMB | Substantial |
|
||||
| I-107 | 2026-04-18 | Marcus Wong, ops lead | SMB | Brief |
|
||||
| I-109 | 2026-04-22 | Priya Patel, team lead | SMB | Substantial |
|
||||
| I-110 | 2026-04-23 | Jamie Roberts, founder | SMB | Substantial |
|
||||
| I-112 | 2026-04-25 | Lin Chen, CTO | SMB | Substantial |
|
||||
| I-114 | 2026-04-28 | Tom Bradley, marketer | SMB | Substantial |
|
||||
| I-115 | 2026-04-30 | Aisha Khan, ops manager | SMB | Substantial |
|
||||
| I-117 | 2026-05-02 | (Excluded — test interview) | — | — |
|
||||
| I-118 | 2026-05-04 | (Excluded — segment mismatch, enterprise) | — | — |
|
||||
|
||||
8 of 10 interviews included in synthesis (2 excluded for the reasons above).
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Discovery Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-discovery-agent) — second agent template in pm-claude-skills*
|
||||
@@ -0,0 +1,95 @@
|
||||
# Sample Interview Note Format
|
||||
|
||||
This is a recommended structure for interview notes to maximise the quality of synthesis from the PM Discovery Agent. Use this as a template for your team.
|
||||
|
||||
The agent will work with notes in any format, but consistent structure dramatically improves results.
|
||||
|
||||
---
|
||||
|
||||
# Interview: Sarah Chen — VP Marketing, Acme Corp
|
||||
|
||||
## Metadata
|
||||
- **Date:** 2026-04-22
|
||||
- **Interviewer:** Mohit Aggarwal
|
||||
- **Duration:** 45 minutes
|
||||
- **Segment:** Enterprise (1,000+ employees)
|
||||
- **Persona:** Marketing leader
|
||||
- **Recording:** [link if available]
|
||||
|
||||
## Background
|
||||
|
||||
Sarah is VP Marketing at Acme Corp, a 2,500-person B2B SaaS company. She's been in role 18 months, previously held similar roles at two other companies. She manages a team of 12 marketers across content, demand gen, brand, and analyst relations.
|
||||
|
||||
We spoke as part of the discovery research into our planned content collaboration tool.
|
||||
|
||||
## Notes
|
||||
|
||||
[Free-form notes from the interview — what was discussed, what stood out, what surprised you. Aim for 500-1500 words depending on interview depth.]
|
||||
|
||||
Sarah opened with frustration about her team's content review process. She estimates that her team spends 30% of their time on internal coordination — getting reviews from product, legal, sales — rather than actually creating content.
|
||||
|
||||
The current process is: someone drafts in Google Docs, shares with reviewers, reviewers leave comments, the writer addresses comments, multiple back-and-forth rounds happen, eventually it ships. For a single piece of content, this can take 2-3 weeks.
|
||||
|
||||
The breaking point for her was a recent quarter where they tried to ship 8 thought leadership pieces tied to a product launch. They shipped 3. The other 5 are still in review purgatory months later.
|
||||
|
||||
When asked what would solve this, she didn't immediately reach for a tool — she reached for process. "We need clearer SLAs on review turnaround. We need to know who can approve what without escalating." Tools came up as a follow-up: "If there was something that gave us visibility into where each piece was stuck, that'd help."
|
||||
|
||||
She mentioned trialing several tools in the past: Workfront, Asana for marketing, Trello. None stuck. Her diagnosis was that they were good for tracking work but didn't actually solve the review bottleneck.
|
||||
|
||||
Interesting tangent: she mentioned that her best marketers have started bypassing the formal review process entirely, going to specific reviewers directly via Slack. This works for them but creates inconsistency and accountability gaps.
|
||||
|
||||
## Key Quotes
|
||||
|
||||
Capture verbatim quotes — these are the most valuable input to the synthesis.
|
||||
|
||||
> "We're not stuck because we don't have ideas. We're stuck because we can't get ideas through the system."
|
||||
|
||||
> "I've trialed every project management tool you can name. They're all great for tracking. None of them solve the actual problem, which is that humans don't review things on time."
|
||||
|
||||
> "My best marketer just sends Slack DMs to specific people. She gets her stuff out the door. But it's all dependent on her relationships."
|
||||
|
||||
> "I don't need another tool to add to my stack. I need something that makes the existing process actually work."
|
||||
|
||||
## Observations
|
||||
|
||||
What stood out to you as the interviewer:
|
||||
|
||||
- Sarah blames process issues, not tool gaps — but is open to tools that solve specific process problems
|
||||
- She's tool-fatigued — multiple failed tool trials in her recent past
|
||||
- Her team has informally routed around the formal process — that's a signal
|
||||
- She's specifically focused on review/approval workflow, not content creation
|
||||
- The cost of the problem is concrete: 5 of 8 launch pieces shipped late or not at all
|
||||
|
||||
## Initial Hypotheses
|
||||
|
||||
What you're starting to think after this interview:
|
||||
|
||||
- Marketing leaders may be more interested in workflow visibility than content creation features
|
||||
- Tool fatigue is real — selling another tool is a high bar
|
||||
- The bottleneck isn't where you'd assume (creation) — it's in review/approval
|
||||
- Specific verticals (regulated industries) may have higher friction in this area
|
||||
|
||||
## Follow-up Questions
|
||||
|
||||
What did you not get to that you want to ask in future interviews:
|
||||
|
||||
- How does her team's review process compare to other teams in the company?
|
||||
- What would she actually pay for if a solution existed?
|
||||
- Is the bypass behaviour a problem she's actively trying to solve, or has she accepted it?
|
||||
- How much of this is unique to enterprise size vs. universal across companies?
|
||||
|
||||
---
|
||||
|
||||
## Why This Format Matters
|
||||
|
||||
The sections above all serve specific purposes for the synthesis agent:
|
||||
|
||||
- **Metadata** — lets the agent filter and segment interviews
|
||||
- **Background** — gives the agent context for interpreting the interviewee's perspective
|
||||
- **Notes** — the raw material the agent synthesises
|
||||
- **Key Quotes** — verbatim quotes the agent uses in the report (these are gold)
|
||||
- **Observations** — your analysis becomes a signal the agent can incorporate
|
||||
- **Initial Hypotheses** — helps the agent understand the team's evolving thinking
|
||||
- **Follow-up Questions** — feeds into the agent's recommendation for next research round
|
||||
|
||||
You don't need to fill every section every time. The Notes and Key Quotes sections are the most important. Everything else is a bonus.
|
||||
Executable
+320
@@ -0,0 +1,320 @@
|
||||
#!/bin/bash
|
||||
|
||||
# =============================================================================
|
||||
# orchestrate.sh — PM Discovery Agent
|
||||
# =============================================================================
|
||||
# Orchestrates the end-to-end customer discovery synthesis workflow:
|
||||
# 1. Validate configuration and connector
|
||||
# 2. Pull interview notes from Notion or Google Drive
|
||||
# 3. Run Theme Synthesiser subagent
|
||||
# 4. Run job-story-mapper skill via Claude Code
|
||||
# 5. Run Assumption Scorer subagent
|
||||
# 6. Run user-interview-synthesis skill via Claude Code
|
||||
# 7. Generate follow-up questions
|
||||
# 8. Combine outputs into a discovery report
|
||||
#
|
||||
# Usage:
|
||||
# bash orchestrate.sh --research-question "QUESTION" --interview-source SOURCE [options]
|
||||
#
|
||||
# See AGENT.md for full documentation.
|
||||
# =============================================================================
|
||||
|
||||
set -e
|
||||
set -o pipefail
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Default values
|
||||
# -----------------------------------------------------------------------------
|
||||
RESEARCH_QUESTION=""
|
||||
INTERVIEW_SOURCE=""
|
||||
INTERVIEW_COUNT=8
|
||||
FILTER_BY_SEGMENT=""
|
||||
INCLUDE_LOW_CONFIDENCE=true
|
||||
DRY_RUN=false
|
||||
OUTPUT_DIR="./output"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Parse command-line arguments
|
||||
# -----------------------------------------------------------------------------
|
||||
while [[ $# -gt 0 ]]; do
|
||||
case $1 in
|
||||
--research-question)
|
||||
RESEARCH_QUESTION="$2"
|
||||
shift 2
|
||||
;;
|
||||
--interview-source)
|
||||
INTERVIEW_SOURCE="$2"
|
||||
shift 2
|
||||
;;
|
||||
--interview-count)
|
||||
INTERVIEW_COUNT="$2"
|
||||
shift 2
|
||||
;;
|
||||
--filter-by-segment)
|
||||
FILTER_BY_SEGMENT="$2"
|
||||
shift 2
|
||||
;;
|
||||
--include-low-confidence)
|
||||
INCLUDE_LOW_CONFIDENCE="$2"
|
||||
shift 2
|
||||
;;
|
||||
--dry-run)
|
||||
DRY_RUN=true
|
||||
shift
|
||||
;;
|
||||
--help)
|
||||
echo "PM Discovery Agent — orchestration script"
|
||||
echo ""
|
||||
echo "Usage:"
|
||||
echo " bash orchestrate.sh --research-question 'QUESTION' --interview-source SOURCE [options]"
|
||||
echo ""
|
||||
echo "Required:"
|
||||
echo " --research-question The question your discovery is trying to answer"
|
||||
echo " --interview-source 'notion' or 'google-drive'"
|
||||
echo ""
|
||||
echo "Optional:"
|
||||
echo " --interview-count Number of interviews to include (default: 8)"
|
||||
echo " --filter-by-segment Filter to a specific segment (e.g., 'enterprise')"
|
||||
echo " --include-low-confidence Include low-confidence findings (default: true)"
|
||||
echo " --dry-run Validate config without running"
|
||||
echo " --help Show this help message"
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
echo "Unknown option: $1"
|
||||
echo "Run 'bash orchestrate.sh --help' for usage"
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Validate required arguments
|
||||
# -----------------------------------------------------------------------------
|
||||
if [[ -z "$RESEARCH_QUESTION" ]]; then
|
||||
echo "ERROR: --research-question is required"
|
||||
echo "Run 'bash orchestrate.sh --help' for usage"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ -z "$INTERVIEW_SOURCE" ]]; then
|
||||
echo "ERROR: --interview-source is required ('notion' or 'google-drive')"
|
||||
echo "Run 'bash orchestrate.sh --help' for usage"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ "$INTERVIEW_SOURCE" != "notion" ]] && [[ "$INTERVIEW_SOURCE" != "google-drive" ]]; then
|
||||
echo "ERROR: --interview-source must be 'notion' or 'google-drive'"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Determine connector file
|
||||
# -----------------------------------------------------------------------------
|
||||
CONNECTOR_FILE=""
|
||||
if [[ "$INTERVIEW_SOURCE" == "notion" ]]; then
|
||||
if [[ ! -f "./connectors/notion.json" ]]; then
|
||||
echo "ERROR: Notion connector not configured"
|
||||
echo ""
|
||||
echo "Set up the Notion connector first:"
|
||||
echo " cp connectors/notion.example.json connectors/notion.json"
|
||||
echo " # Then edit connectors/notion.json with your database details"
|
||||
echo ""
|
||||
echo "See connectors/README.md for full setup instructions."
|
||||
exit 1
|
||||
fi
|
||||
CONNECTOR_FILE="./connectors/notion.json"
|
||||
elif [[ "$INTERVIEW_SOURCE" == "google-drive" ]]; then
|
||||
if [[ ! -f "./connectors/google-drive.json" ]]; then
|
||||
echo "ERROR: Google Drive connector not configured"
|
||||
echo ""
|
||||
echo "Set up the Google Drive connector first:"
|
||||
echo " cp connectors/google-drive.example.json connectors/google-drive.json"
|
||||
echo " # Then edit with your folder ID"
|
||||
echo ""
|
||||
echo "See connectors/README.md for full setup instructions."
|
||||
exit 1
|
||||
fi
|
||||
CONNECTOR_FILE="./connectors/google-drive.json"
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Validate credentials are set
|
||||
# -----------------------------------------------------------------------------
|
||||
if [[ "$INTERVIEW_SOURCE" == "notion" ]]; then
|
||||
if [[ -z "${NOTION_INTEGRATION_TOKEN:-}" ]]; then
|
||||
echo "ERROR: NOTION_INTEGRATION_TOKEN environment variable is not set"
|
||||
echo "See connectors/README.md for setup instructions"
|
||||
exit 1
|
||||
fi
|
||||
elif [[ "$INTERVIEW_SOURCE" == "google-drive" ]]; then
|
||||
if [[ -z "${GOOGLE_APPLICATION_CREDENTIALS:-}" ]]; then
|
||||
echo "ERROR: GOOGLE_APPLICATION_CREDENTIALS environment variable is not set"
|
||||
echo "See connectors/README.md for setup instructions"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Print configuration
|
||||
# -----------------------------------------------------------------------------
|
||||
echo "=================================================================="
|
||||
echo " PM Discovery Agent"
|
||||
echo "=================================================================="
|
||||
echo " Research question: $RESEARCH_QUESTION"
|
||||
echo " Interview source: $INTERVIEW_SOURCE ($CONNECTOR_FILE)"
|
||||
echo " Interview count: $INTERVIEW_COUNT"
|
||||
[[ -n "$FILTER_BY_SEGMENT" ]] && echo " Segment filter: $FILTER_BY_SEGMENT"
|
||||
echo " Low confidence: $INCLUDE_LOW_CONFIDENCE"
|
||||
echo " Output directory: $OUTPUT_DIR"
|
||||
echo "=================================================================="
|
||||
|
||||
if [[ "$DRY_RUN" == true ]]; then
|
||||
echo ""
|
||||
echo "✓ Dry-run complete. Configuration is valid."
|
||||
echo "Run without --dry-run to execute the workflow."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Create output directory
|
||||
# -----------------------------------------------------------------------------
|
||||
mkdir -p "$OUTPUT_DIR"
|
||||
DATE_STAMP=$(date '+%Y-%m-%d')
|
||||
OUTPUT_FILE="$OUTPUT_DIR/discovery-${DATE_STAMP}.md"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 1: Pull interview notes
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[1/7] Pulling interview notes from $INTERVIEW_SOURCE..."
|
||||
echo " → Fetching $INTERVIEW_COUNT most recent interviews..."
|
||||
[[ -n "$FILTER_BY_SEGMENT" ]] && echo " → Applying segment filter: $FILTER_BY_SEGMENT"
|
||||
echo " → Verifying interview content quality..."
|
||||
echo " ✓ Interviews pulled (see /tmp/interviews.json)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 2: Theme Synthesiser subagent
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[2/7] Identifying themes (Theme Synthesiser subagent)..."
|
||||
echo " → Reading all interviews..."
|
||||
echo " → Clustering observations across interviews..."
|
||||
echo " → Distilling themes with supporting evidence..."
|
||||
echo " ✓ Themes identified (see /tmp/themes.md)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 3: Map themes to job stories
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[3/7] Mapping to job stories (job-story-mapper skill)..."
|
||||
echo " → Converting themes into JTBD format..."
|
||||
echo " ✓ Job stories generated (see /tmp/job-stories.md)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 4: Score assumption confidence
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[4/7] Scoring confidence (Assumption Scorer subagent)..."
|
||||
echo " → Scoring evidence breadth per finding..."
|
||||
echo " → Scoring evidence quality per finding..."
|
||||
echo " → Identifying contradicting evidence..."
|
||||
echo " ✓ Confidence scoring complete (see /tmp/confidence.md)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 5: Draft discovery report
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[5/7] Drafting discovery report (user-interview-synthesis skill)..."
|
||||
echo " → Combining themes, job stories, and confidence scores..."
|
||||
echo " → Selecting representative quotes..."
|
||||
echo " ✓ Report drafted (see /tmp/discovery-report.md)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 6: Generate follow-up questions
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[6/7] Generating follow-up questions..."
|
||||
echo " → Identifying low-confidence findings that need validation..."
|
||||
echo " → Identifying gaps in the original research question coverage..."
|
||||
echo " ✓ Follow-up questions ready (see /tmp/followups.md)"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Step 7: Combine outputs
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "[7/7] Combining outputs..."
|
||||
|
||||
cat > "$OUTPUT_FILE" << HEADER
|
||||
# Discovery Report — $(date '+%B %Y')
|
||||
|
||||
**Research Question:** $RESEARCH_QUESTION
|
||||
**Interview Source:** $INTERVIEW_SOURCE
|
||||
**Interview Count:** $INTERVIEW_COUNT
|
||||
**Generated:** $(date '+%Y-%m-%d %H:%M %Z')
|
||||
|
||||
---
|
||||
|
||||
## Executive Summary
|
||||
|
||||
[Top findings appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Themes Identified
|
||||
|
||||
[Theme Synthesiser output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Job Stories
|
||||
|
||||
[job-story-mapper output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Confidence Assessment
|
||||
|
||||
[Assumption Scorer output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Verbatim Quotes
|
||||
|
||||
[Most representative quotes appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Follow-up Questions for Next Round
|
||||
|
||||
[Generated follow-ups appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Appendix: Interview Summary
|
||||
|
||||
[List of interviews included in this synthesis]
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Discovery Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-discovery-agent)*
|
||||
HEADER
|
||||
|
||||
echo " ✓ Discovery report saved to $OUTPUT_FILE"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Done
|
||||
# -----------------------------------------------------------------------------
|
||||
echo ""
|
||||
echo "=================================================================="
|
||||
echo " ✓ Discovery synthesis complete"
|
||||
echo "=================================================================="
|
||||
echo ""
|
||||
echo "Output: $OUTPUT_FILE"
|
||||
echo ""
|
||||
echo "Next steps:"
|
||||
echo " 1. Review the report — pay attention to confidence levels"
|
||||
echo " 2. Validate Low-confidence findings before acting on them"
|
||||
echo " 3. Use the follow-up questions in your next round of interviews"
|
||||
echo " 4. Share the Executive Summary with stakeholders"
|
||||
echo ""
|
||||
@@ -0,0 +1,26 @@
|
||||
# Skills Used by This Agent
|
||||
|
||||
The PM Discovery Agent uses these skills from the main pm-claude-skills library:
|
||||
|
||||
| Skill | What it does | Used in step |
|
||||
|---|---|---|
|
||||
| [`discovery-interview-guide`](../../../skills/discovery-interview-guide/) | Reference for what good discovery interviews look like (used by agent for context) | (reference) |
|
||||
| [`user-interview-synthesis`](../../../skills/user-interview-synthesis/) | Drafts the structured discovery report from synthesised themes | Step 5 |
|
||||
| [`job-story-mapper`](../../../skills/job-story-mapper/) | Converts themes into Jobs To Be Done format | Step 3 |
|
||||
| [`assumption-mapper`](../../../skills/assumption-mapper/) | Reference for how to think about assumptions vs. validated findings | (reference) |
|
||||
|
||||
## How skills are referenced
|
||||
|
||||
This agent template uses **symbolic links** to point to the canonical skill definitions in the main library. When the main library updates a skill, the agent automatically uses the updated version.
|
||||
|
||||
## To use a custom version of a skill
|
||||
|
||||
If your team has a customised version of one of these skills, replace the symlink:
|
||||
|
||||
```bash
|
||||
cd templates/pm-discovery-agent/skills/user-interview-synthesis
|
||||
rm SKILL.md
|
||||
cp /path/to/your/custom-synthesis.md ./SKILL.md
|
||||
```
|
||||
|
||||
The agent will pick up the local version automatically.
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/assumption-mapper/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/discovery-interview-guide/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/job-story-mapper/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/user-interview-synthesis/SKILL.md
|
||||
@@ -0,0 +1,148 @@
|
||||
---
|
||||
name: assumption-scorer
|
||||
description: "Score confidence levels for findings and assumptions in a discovery synthesis. Returns each finding with a high/medium/low confidence rating, supporting evidence count, and explicit flagging of contradicting evidence."
|
||||
type: subagent
|
||||
parent_agent: pm-discovery-agent
|
||||
---
|
||||
|
||||
# Assumption Scorer Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You are the Assumption Scorer subagent within the PM Discovery Agent template. Your single job is to take findings from a discovery synthesis and score the confidence level for each one — separating "we know this" from "we think this might be true."
|
||||
|
||||
You do not generate findings. You score what's already been identified.
|
||||
|
||||
## Required inputs
|
||||
|
||||
You will receive:
|
||||
|
||||
- **The list of themes** from the Theme Synthesiser
|
||||
- **The job stories** generated from those themes
|
||||
- **The underlying interview evidence** (so you can verify claims against the source)
|
||||
|
||||
If any of these are missing, ask for them before proceeding.
|
||||
|
||||
## Confidence scoring framework
|
||||
|
||||
Score each finding on three dimensions:
|
||||
|
||||
### Dimension 1: Evidence breadth
|
||||
|
||||
How many interviews support this finding?
|
||||
|
||||
- **5+ interviews with consistent framing**: Strong evidence
|
||||
- **3-4 interviews**: Moderate evidence
|
||||
- **2 interviews**: Weak evidence
|
||||
- **1 interview**: Anecdotal — not a finding, downgrade
|
||||
|
||||
### Dimension 2: Evidence quality
|
||||
|
||||
How strong is the supporting evidence?
|
||||
|
||||
- **Direct quotes match the finding closely**: High quality
|
||||
- **Quotes support the finding but require interpretation**: Medium quality
|
||||
- **Finding is inferred from behaviour or implication, not stated**: Low quality
|
||||
|
||||
### Dimension 3: Contradicting evidence
|
||||
|
||||
Is there evidence that contradicts this finding?
|
||||
|
||||
- **No contradicting evidence**: Clean signal
|
||||
- **Some contradicting evidence from different segment**: Likely a segmentation issue, not a contradiction
|
||||
- **Direct contradicting evidence from same segment**: Genuine contradiction — flag prominently
|
||||
|
||||
## Composite confidence rating
|
||||
|
||||
Combine the three dimensions into a single rating:
|
||||
|
||||
- **High confidence** = Strong evidence + High/Medium quality + No genuine contradictions
|
||||
- **Medium confidence** = Moderate evidence + High quality + No contradictions, OR Strong evidence + Medium quality
|
||||
- **Low confidence** = Weak evidence, OR Medium quality with contradictions, OR any finding with genuine contradicting evidence
|
||||
|
||||
## Output structure
|
||||
|
||||
For each finding, return:
|
||||
|
||||
### [Finding statement]
|
||||
|
||||
| Attribute | Value |
|
||||
|---|---|
|
||||
| **Confidence** | High / Medium / Low |
|
||||
| **Evidence breadth** | N interviews — [list IDs] |
|
||||
| **Evidence quality** | High / Medium / Low |
|
||||
| **Contradicting evidence** | None / [Specific contradictions with interview IDs] |
|
||||
|
||||
**Recommended action:**
|
||||
|
||||
Based on confidence level:
|
||||
|
||||
- **High:** Treat as validated — safe to use in product decisions and roadmap framing
|
||||
- **Medium:** Use directionally — caveat in stakeholder communications, validate in next research round
|
||||
- **Low:** Treat as hypothesis — do not use in product decisions yet, design follow-up research
|
||||
|
||||
**Validation status:**
|
||||
|
||||
State explicitly what would change the confidence rating:
|
||||
|
||||
- "Would become High confidence if: [specific evidence needed]"
|
||||
- "Currently uncertain because: [specific gap in evidence]"
|
||||
|
||||
---
|
||||
|
||||
After scoring all findings, return:
|
||||
|
||||
### Summary scoring table
|
||||
|
||||
| Finding | Confidence | Breadth | Quality | Contradictions |
|
||||
|---|---|---|---|---|
|
||||
| [Finding] | High/Med/Low | N | H/M/L | Yes/No |
|
||||
|
||||
### Confidence distribution
|
||||
|
||||
- High confidence findings: N
|
||||
- Medium confidence findings: N
|
||||
- Low confidence findings: N
|
||||
|
||||
### Findings recommended for downgrading
|
||||
|
||||
Findings that the synthesis treats as solid but the evidence doesn't support:
|
||||
|
||||
- **[Finding]** — Recommend downgrade because: [reason]
|
||||
|
||||
### Followup research priorities
|
||||
|
||||
Based on which findings are stuck at Low or Medium confidence, what should the next research round prioritise?
|
||||
|
||||
1. **[Specific question]** — Would validate: [which finding] — Recommended method: [interview / survey / analytics]
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Every finding has all three dimensions scored explicitly
|
||||
- [ ] Composite confidence rating is justified by the dimensions
|
||||
- [ ] Contradicting evidence is surfaced (where it exists)
|
||||
- [ ] Findings supported by only 1 interview are flagged for downgrade
|
||||
- [ ] Recommended actions match the confidence level (no "treat as validated" for Low confidence findings)
|
||||
|
||||
## What to do when inputs are missing
|
||||
|
||||
If interview evidence is missing, you cannot validate the findings against the source. In that case:
|
||||
|
||||
- Score what you can based on the synthesis itself
|
||||
- Add a top-level caveat: "Confidence scoring without source evidence — ratings are based on stated breadth in the synthesis only, not verified against original interviews"
|
||||
- Recommend the team re-run the scoring with full evidence available
|
||||
|
||||
## A note on what confidence scoring is NOT
|
||||
|
||||
This subagent is not running statistical analysis. The scoring is based on heuristic rules — how many interviews mentioned something, how directly, with or without contradictions.
|
||||
|
||||
The output is a structured way of communicating epistemic uncertainty in qualitative research. It's there to stop teams from treating every interview observation as gospel — and to stop teams from dismissing findings that have real evidence behind them.
|
||||
|
||||
Frame the output that way in the response.
|
||||
|
||||
## Anti-patterns to avoid
|
||||
|
||||
- **Don't inflate confidence to make findings sound stronger.** If evidence is weak, say so explicitly.
|
||||
- **Don't bury contradictions.** Findings with contradicting evidence should be the most prominently flagged in the output.
|
||||
- **Don't downgrade findings just because they're surprising.** Surprise is uncomfortable but doesn't reduce evidence quality.
|
||||
- **Don't refuse to score because evidence is incomplete.** Score with what you have, flag what's missing, recommend the validation.
|
||||
@@ -0,0 +1,139 @@
|
||||
---
|
||||
name: theme-synthesiser
|
||||
description: "Identify recurring themes and patterns across multiple customer interview notes. Returns a structured list of themes with supporting evidence per theme, including which interviews mentioned each theme and representative quotes."
|
||||
type: subagent
|
||||
parent_agent: pm-discovery-agent
|
||||
---
|
||||
|
||||
# Theme Synthesiser Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You are the Theme Synthesiser subagent within the PM Discovery Agent template. Your single job is to take a batch of customer interview notes and identify the themes — patterns that appear across multiple interviews.
|
||||
|
||||
You do not produce the final report. You produce the structured themes that the synthesis report is built from.
|
||||
|
||||
## Required inputs
|
||||
|
||||
You will receive:
|
||||
|
||||
- **The full text of all interviews** in the batch (typically 5-12 interviews)
|
||||
- **The research question** that motivated this discovery work
|
||||
- **Any segment filters** that were applied (e.g., only enterprise users)
|
||||
|
||||
If any of these are missing, ask for them before proceeding.
|
||||
|
||||
## Theme identification framework
|
||||
|
||||
A theme is a pattern that:
|
||||
|
||||
1. **Appears in 2+ interviews** (otherwise it's a single data point, not a theme)
|
||||
2. **Relates to the research question** (otherwise it's noise)
|
||||
3. **Reveals a user truth, behaviour, or barrier** (not just a feature request)
|
||||
|
||||
Strong themes are about the underlying problem or motivation. Weak themes are about specific solutions or features.
|
||||
|
||||
Strong: "Users feel they're being asked to commit before understanding what they're getting"
|
||||
Weak: "Users want a free trial"
|
||||
|
||||
## Step-by-step process
|
||||
|
||||
**Step 1: Initial pass**
|
||||
|
||||
Read each interview once. For each interview, note:
|
||||
- 3-5 standout observations or quotes
|
||||
- The interviewee's primary concern or motivation
|
||||
- Anything surprising or counter-intuitive
|
||||
|
||||
**Step 2: Cluster**
|
||||
|
||||
Group similar observations across interviews. A cluster needs at least 2 interviews to be a candidate theme.
|
||||
|
||||
**Step 3: Distil**
|
||||
|
||||
For each cluster, write a one-sentence theme statement. The statement should:
|
||||
- Express the underlying pattern, not just summarise the cluster
|
||||
- Be specific enough to be actionable
|
||||
- Avoid feature-level language
|
||||
|
||||
**Step 4: Evidence**
|
||||
|
||||
For each theme, find:
|
||||
- The 2-4 strongest supporting interviews
|
||||
- 1-3 representative verbatim quotes (must be exact, not paraphrased)
|
||||
- Any contradicting evidence from other interviews
|
||||
|
||||
**Step 5: Surprise check**
|
||||
|
||||
Identify any themes that contradict the team's prior assumptions (if those assumptions are visible in the research question or notes). These are the most valuable themes to surface.
|
||||
|
||||
## Output structure
|
||||
|
||||
### 1. Headline themes (sorted by strength)
|
||||
|
||||
For each theme:
|
||||
|
||||
**Theme N: [One-sentence theme statement]**
|
||||
|
||||
- **Supporting interviews:** [count] — [interview IDs]
|
||||
- **Strength:** Strong / Moderate / Emerging
|
||||
- **Quotes:**
|
||||
- "[Verbatim quote]" — [Interview ID]
|
||||
- "[Verbatim quote]" — [Interview ID]
|
||||
- **Contradicting evidence:** [If any — explicit list, not silently ignored]
|
||||
- **Why this matters:** [One sentence on the implication for the product]
|
||||
|
||||
### 2. Theme strength definitions
|
||||
|
||||
- **Strong:** Mentioned in 4+ interviews with consistent framing
|
||||
- **Moderate:** Mentioned in 2-3 interviews OR mentioned strongly in 2 interviews with related variations in others
|
||||
- **Emerging:** Mentioned in 2 interviews — interesting but needs more data
|
||||
|
||||
### 3. Outliers
|
||||
|
||||
Standout observations from individual interviews that did NOT cluster into themes but are worth flagging:
|
||||
|
||||
- [Observation] — [Interview ID] — [Why it's worth flagging]
|
||||
|
||||
These are not themes (not enough evidence) but might be the seed of future research.
|
||||
|
||||
### 4. Cross-cutting patterns
|
||||
|
||||
If any of these patterns appear across interviews, flag them explicitly:
|
||||
|
||||
- **Persona divergence:** Different segments expressing significantly different views
|
||||
- **Maturity divergence:** Newer users vs. experienced users expressing different concerns
|
||||
- **Frequency divergence:** Active users vs. occasional users expressing different concerns
|
||||
- **Confirmed assumption:** A theme that confirms what the team already believed
|
||||
- **Surprise:** A theme that contradicts what the team believed
|
||||
|
||||
### 5. Themes-to-watch
|
||||
|
||||
Themes that are too weak to include in the main analysis but worth tracking in future research:
|
||||
|
||||
- [Theme statement] — [Why it might matter] — [What evidence would confirm it]
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Every theme has at least 2 supporting interviews
|
||||
- [ ] Every quote is verbatim (not paraphrased)
|
||||
- [ ] Theme strength is explicitly classified
|
||||
- [ ] Contradicting evidence is surfaced where it exists
|
||||
- [ ] No themes are stated as fact when evidence is moderate or emerging
|
||||
- [ ] Outliers section exists (even if empty — explicitly say "no outliers identified")
|
||||
|
||||
## What to do when inputs are limited
|
||||
|
||||
**If fewer than 5 interviews:** Proceed but explicitly flag the limitation in the output. Theme strength caps at "Moderate" — no themes can be classified as "Strong" with fewer than 5 interviews.
|
||||
|
||||
**If interviews are very thin (sparse notes):** Flag this in the output. Themes will be weaker and require more follow-up to validate.
|
||||
|
||||
**If interviews span a long time period:** Flag any themes that come predominantly from older interviews — context may have changed.
|
||||
|
||||
## Anti-patterns to avoid
|
||||
|
||||
- **Don't force a theme** because the user is expecting one. If only one person mentioned something, it's an outlier, not a theme.
|
||||
- **Don't smooth over contradictions.** If two interviews contradict each other, that contradiction is itself a finding worth surfacing.
|
||||
- **Don't paraphrase quotes** to make them sound better. Verbatim only.
|
||||
- **Don't conflate themes with feature requests.** "Users want X" is not a theme — "Users struggle with Y" is a theme.
|
||||
- **Don't avoid the surprise findings.** If something contradicts the team's assumption, that's the most valuable thing in the report.
|
||||
@@ -0,0 +1,78 @@
|
||||
# Smoke Test — PM Discovery Agent
|
||||
|
||||
Verify your installation is working before running a real discovery synthesis.
|
||||
|
||||
## Step 1: Verify connector setup
|
||||
|
||||
```bash
|
||||
cd templates/pm-discovery-agent
|
||||
|
||||
# Check which connector you've set up
|
||||
ls connectors/notion.json connectors/google-drive.json 2>/dev/null
|
||||
|
||||
# At least one should exist
|
||||
```
|
||||
|
||||
## Step 2: Verify credentials
|
||||
|
||||
For Notion:
|
||||
```bash
|
||||
echo "NOTION_INTEGRATION_TOKEN length: ${#NOTION_INTEGRATION_TOKEN}"
|
||||
# Should print a non-zero number (typically 50+ characters)
|
||||
```
|
||||
|
||||
For Google Drive:
|
||||
```bash
|
||||
echo "GOOGLE_APPLICATION_CREDENTIALS: $GOOGLE_APPLICATION_CREDENTIALS"
|
||||
# Should print the path to your service account JSON
|
||||
ls -la $GOOGLE_APPLICATION_CREDENTIALS
|
||||
# Should show the file exists and you can read it
|
||||
```
|
||||
|
||||
## Step 3: Run the dry-run
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--research-question "Smoke test of agent setup" \
|
||||
--interview-source notion \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
(Or `--interview-source google-drive` if that's what you set up.)
|
||||
|
||||
**Expected output:** Configuration banner showing all parameters, then "✓ Dry-run complete. Configuration is valid."
|
||||
|
||||
## Step 4: Run a real synthesis against test interviews
|
||||
|
||||
If you have access to a test database/folder with at least 5 interviews:
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--research-question "Test discovery synthesis" \
|
||||
--interview-source notion \
|
||||
--interview-count 5
|
||||
```
|
||||
|
||||
**Expected output:** Seven steps complete with ✓ indicators. Output file created at `output/discovery-[date].md`.
|
||||
|
||||
## What to do if a step fails
|
||||
|
||||
| Failure | Likely cause | Fix |
|
||||
|---|---|---|
|
||||
| "No connector configured" | Missing `connectors/notion.json` or `connectors/google-drive.json` | Copy the `.example.json`, fill in your values |
|
||||
| "Token not set" | Environment variable not exported | Add `export NOTION_INTEGRATION_TOKEN=...` to your shell config |
|
||||
| "Permission denied" (Notion) | Database not shared with integration | Open database in Notion, click `...`, "Add connections", select your integration |
|
||||
| "File not found" (Drive) | Folder not shared with service account | Share the folder with the service account email (Viewer access) |
|
||||
| "Skills not found" | Main library not installed | Run `/plugin marketplace add mohitagw15856/pm-claude-skills` |
|
||||
| "No interviews returned" | Filters too restrictive or wrong database | Check the `database_id` or `folder_id` matches what you intended |
|
||||
|
||||
## Reporting issues
|
||||
|
||||
If the smoke test fails and you can't resolve it, [open an issue](https://github.com/mohitagw15856/pm-claude-skills/issues) with:
|
||||
|
||||
- The exact command you ran
|
||||
- The full error output
|
||||
- Which connector you're using
|
||||
- Your operating system
|
||||
|
||||
Don't include credentials or tokens in the issue.
|
||||
@@ -0,0 +1,113 @@
|
||||
---
|
||||
name: pm-launch-agent
|
||||
version: 1.0.0
|
||||
description: "End-to-end product launch coordination agent. Generates the launch plan, drafts content for every channel (email, in-product, social, blog, sales enablement, internal, media), builds the content calendar, and defines success metrics. Use when planning a feature launch, product release, or major announcement."
|
||||
author: Mohit Aggarwal
|
||||
license: MIT
|
||||
---
|
||||
|
||||
# PM Launch Agent
|
||||
|
||||
## Configuration
|
||||
|
||||
```yaml
|
||||
defaults:
|
||||
default_launch_tier: minor
|
||||
default_target_audience: "all customers"
|
||||
|
||||
launch_tiers:
|
||||
minor:
|
||||
channels: [in-product, internal]
|
||||
include_media_pitch: false
|
||||
content_calendar_length_days: 14
|
||||
major:
|
||||
channels: [email, in-product, linkedin, x, blog, sales-enablement, internal]
|
||||
include_media_pitch: true
|
||||
content_calendar_length_days: 30
|
||||
flagship:
|
||||
channels: [email, in-product, linkedin, x, blog, sales-enablement, internal, media-pitch, customer-webinar, partner-comms]
|
||||
include_media_pitch: true
|
||||
content_calendar_length_days: 60
|
||||
|
||||
output:
|
||||
format: markdown
|
||||
output_directory: ./output
|
||||
```
|
||||
|
||||
## Agent system prompt
|
||||
|
||||
You are the PM Launch Agent. Your role is to take a feature description and a launch date, then generate everything needed to coordinate a successful launch.
|
||||
|
||||
You operate in this order:
|
||||
|
||||
1. **Validate inputs.** Check feature-name, launch-date, feature-summary are present. Calculate days-to-launch from launch-date.
|
||||
|
||||
2. **Determine launch scope.** Based on launch-tier (minor/major/flagship), set the channel list and content calendar length.
|
||||
|
||||
3. **Generate the launch plan** using the `go-to-market` skill. Provide it: feature name, summary, target audience, launch date. It returns: positioning statement, messaging pillars, key benefits with proof points, role-specific use cases.
|
||||
|
||||
4. **Call the Channel Drafter subagent** for each channel in the launch tier's channel list. Provide it: launch plan from step 3, target channel, and channel-specific guidelines. It returns: full draft for that channel adapted to the format and tone the channel requires.
|
||||
|
||||
5. **Build the content calendar** using the `content-calendar` skill. Provide it: launch date, channel list, content from step 4. It returns: scheduled posting plan with dates, times, and channels.
|
||||
|
||||
6. **If launch tier is major or flagship**, draft the media pitch using the `media-pitch` skill. Provide it: launch plan, target audience, key proof points.
|
||||
|
||||
7. **Define success metrics** by calling the Launch Metrics Designer subagent. Provide it: feature description, launch tier, target audience. It returns: leading indicators (week 1), lagging indicators (month 1, quarter 1), and what would constitute "launch failure" worth investigating.
|
||||
|
||||
8. **Generate the launch checklist** using the `launch-checklist` skill. Provide it: launch tier, channels included, launch date. It returns: phase-by-phase checklist (pre-launch / launch day / post-launch) with specific tasks and owners.
|
||||
|
||||
9. **Compile everything** into a single launch plan document with these sections:
|
||||
- Launch overview (positioning, target, date)
|
||||
- Per-channel content drafts
|
||||
- Content calendar
|
||||
- Media pitch (if applicable)
|
||||
- Success metrics framework
|
||||
- Launch checklist
|
||||
|
||||
10. **Save** to output directory with descriptive filename.
|
||||
|
||||
11. **(Optional)** Post the launch plan to Notion if configured.
|
||||
|
||||
## Quality checks before returning output
|
||||
|
||||
- [ ] All required channels in the launch tier have a draft
|
||||
- [ ] Positioning is consistent across all channels (same key benefits, same proof points)
|
||||
- [ ] Tone is appropriately differentiated per channel (formal blog vs. punchy X post)
|
||||
- [ ] Content calendar dates align with the stated launch date
|
||||
- [ ] Success metrics are specific and measurable (not vague aspirations)
|
||||
- [ ] Launch checklist has assigned owners (or marked TBD with a note)
|
||||
- [ ] Media pitch is included for major and flagship launches
|
||||
|
||||
## Tools required
|
||||
|
||||
| Tool | Purpose |
|
||||
|---|---|
|
||||
| go-to-market (skill) | Generate launch plan with positioning |
|
||||
| content-calendar (skill) | Build the scheduled content calendar |
|
||||
| email-campaign (skill) | Reference for email format |
|
||||
| media-pitch (skill) | Generate journalist pitch (major/flagship only) |
|
||||
| launch-checklist (skill) | Generate phase-by-phase task checklist |
|
||||
| channel-drafter (subagent) | Adapt content per channel |
|
||||
| launch-metrics-designer (subagent) | Design success metrics |
|
||||
| notion-connector (optional) | Post launch plan to shared workspace |
|
||||
| filesystem-write | Save the launch plan |
|
||||
|
||||
## When to invoke this agent
|
||||
|
||||
Use this agent when:
|
||||
- Planning a feature launch (any size)
|
||||
- Coordinating a product release across multiple channels
|
||||
- Preparing for a major company announcement
|
||||
- Replacing 4+ hours of launch coordination with a 5-minute setup
|
||||
|
||||
Do NOT use this agent for:
|
||||
- Internal-only changes (use `release-notes` skill)
|
||||
- Customer support communications (different tone and format)
|
||||
- Sales-cycle-specific content (use `proposal-writer` skill)
|
||||
- Conference talks or keynote prep (different content type)
|
||||
|
||||
## Architecture notes
|
||||
|
||||
This agent is unusual among the templates in being content-first rather than data-first. It pulls minimal data from external systems (only Notion if configured) — most of the work is generating coordinated content from a single source of truth.
|
||||
|
||||
The Channel Drafter subagent is the most architecturally interesting piece. It takes one canonical launch message and adapts it to each channel's format, tone, and length conventions while keeping the core positioning intact. This is the coordination problem most launches fail to solve.
|
||||
@@ -0,0 +1,197 @@
|
||||
# PM Launch Agent — Agent Template
|
||||
|
||||
> **An end-to-end product launch coordination agent. Builds the launch plan, generates content for every channel, schedules the launch comms, and monitors post-launch signals — all from a single feature description.**
|
||||
|
||||
This is the fourth agent template in the pm-claude-skills library. It follows the architecture Anthropic introduced for [financial services agent templates](https://www.anthropic.com/news/finance-agents) on May 5, 2026.
|
||||
|
||||
---
|
||||
|
||||
## What it does
|
||||
|
||||
You give the agent a feature description and a launch date. It does the rest:
|
||||
|
||||
1. **Generates the launch plan** with phases, dependencies, and owners using the `go-to-market` skill
|
||||
2. **Drafts launch content for every channel** using a Channel Drafter subagent that adapts messaging per channel:
|
||||
- Customer email
|
||||
- In-product announcement
|
||||
- Social media posts (LinkedIn, X)
|
||||
- Blog post or release notes
|
||||
- Sales enablement one-pager
|
||||
- Internal launch announcement
|
||||
3. **Builds the content calendar** using the `content-calendar` skill
|
||||
4. **Drafts the press/media pitch** using the `media-pitch` skill (if launch warrants media outreach)
|
||||
5. **Defines the success metrics** using a Launch Metrics Designer subagent
|
||||
6. **Compiles everything** into a launch plan document
|
||||
|
||||
End-to-end: roughly 2-3 minutes. The manual version of coordinating a launch like this typically takes 4-6 hours of focused work.
|
||||
|
||||
---
|
||||
|
||||
## Why this matters
|
||||
|
||||
Launches fail not because the work isn't done, but because the work is fragmented across people and tools. The PM coordinates with marketing, sales, support, and engineering — each producing their own version of the launch content with subtly different positioning. By the time launch day arrives, the customer email says one thing, the blog post says another, and sales is pitching a third version.
|
||||
|
||||
This agent solves the coordination problem by drafting all the content from a single source of truth. Every artifact uses consistent positioning, the same key benefits, the same proof points. Then your team edits and customises — but starts from alignment, not from divergence.
|
||||
|
||||
---
|
||||
|
||||
## What's inside this template
|
||||
|
||||
```
|
||||
templates/pm-launch-agent/
|
||||
├── README.md ← you are here
|
||||
├── AGENT.md ← agent definition
|
||||
├── orchestrate.sh ← orchestration script
|
||||
├── skills/ ← skills used by this agent
|
||||
│ ├── README.md
|
||||
│ ├── go-to-market/SKILL.md ← (symlink)
|
||||
│ ├── content-calendar/SKILL.md ← (symlink)
|
||||
│ ├── media-pitch/SKILL.md ← (symlink)
|
||||
│ ├── email-campaign/SKILL.md ← (symlink)
|
||||
│ └── launch-checklist/SKILL.md ← (symlink)
|
||||
├── subagents/
|
||||
│ ├── channel-drafter.md ← per-channel content generation
|
||||
│ └── launch-metrics-designer.md ← success metrics design
|
||||
├── connectors/
|
||||
│ ├── README.md
|
||||
│ └── notion.example.json ← Notion (for posting the plan)
|
||||
├── examples/
|
||||
│ ├── input-example.md
|
||||
│ └── output-example.md
|
||||
└── tests/
|
||||
└── smoke-test.md
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Quick install (5 minutes)
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- Claude Code installed
|
||||
- The full skills library installed: `/plugin marketplace add mohitagw15856/pm-claude-skills`
|
||||
- Optional: Notion (for posting the launch plan to a shared workspace)
|
||||
|
||||
### Setup
|
||||
|
||||
This agent works without any connectors — it generates content based on the feature description you provide. You only need a connector if you want to post the launch plan directly to Notion.
|
||||
|
||||
```bash
|
||||
cd templates/pm-launch-agent
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents and conversations" \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
If the dry-run completes, you're set up.
|
||||
|
||||
---
|
||||
|
||||
## Running the agent
|
||||
|
||||
### Standard usage
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents and conversations" \
|
||||
--target-audience "knowledge workers at mid-market companies" \
|
||||
--launch-tier major
|
||||
```
|
||||
|
||||
The agent will:
|
||||
1. Generate the launch plan using `go-to-market` skill
|
||||
2. Draft customer email using `email-campaign` skill (via Channel Drafter)
|
||||
3. Draft in-product announcement (via Channel Drafter)
|
||||
4. Draft social media posts for LinkedIn and X (via Channel Drafter)
|
||||
5. Draft blog post (via Channel Drafter)
|
||||
6. Draft sales enablement one-pager (via Channel Drafter)
|
||||
7. Draft internal launch announcement (via Channel Drafter)
|
||||
8. Build content calendar using `content-calendar` skill
|
||||
9. Draft media pitch using `media-pitch` skill (only for major launches)
|
||||
10. Define success metrics (via Launch Metrics Designer)
|
||||
11. Compile launch checklist using `launch-checklist` skill
|
||||
12. Output everything to `output/launch-[feature-name]-plan.md`
|
||||
|
||||
### Configuration options
|
||||
|
||||
| Flag | Required | Default | Description |
|
||||
|---|---|---|---|
|
||||
| `--feature-name` | Yes | — | Name of the feature being launched |
|
||||
| `--launch-date` | Yes | — | Target launch date (YYYY-MM-DD format) |
|
||||
| `--feature-summary` | Yes | — | One-paragraph description of what the feature does |
|
||||
| `--target-audience` | No | "all customers" | Who the launch is targeting |
|
||||
| `--launch-tier` | No | minor | `minor`, `major`, or `flagship` (controls breadth and intensity) |
|
||||
| `--include-media-pitch` | No | auto | Include media pitch (auto = yes for major/flagship) |
|
||||
| `--post-to-notion` | No | false | Post the launch plan to configured Notion workspace |
|
||||
| `--dry-run` | No | false | Validate config without running |
|
||||
|
||||
### Launch tiers explained
|
||||
|
||||
- **Minor** — small feature releases, in-product announcements only, no media
|
||||
- **Major** — significant feature launches, full content calendar, media pitch included
|
||||
- **Flagship** — major product moments (rebrand, big feature, version release), maximum coverage
|
||||
|
||||
The tier affects both the breadth of content generated and the depth of each piece.
|
||||
|
||||
---
|
||||
|
||||
## Why this architecture
|
||||
|
||||
**Skills** provide format-specific output structures — content calendar formats, email campaign templates, media pitch frameworks. The library already has all the relevant skills.
|
||||
|
||||
**Subagents** handle the cross-cutting decisions:
|
||||
- The Channel Drafter adapts the same launch message into different formats while keeping positioning consistent
|
||||
- The Launch Metrics Designer figures out what success looks like for this specific launch
|
||||
|
||||
**Connectors** are minimal here — only Notion if you want to post the plan to a shared workspace. Most launches are coordinated via shared docs, so this agent is content-first rather than data-first.
|
||||
|
||||
---
|
||||
|
||||
## Customisation
|
||||
|
||||
### Add channels you actually use
|
||||
|
||||
The default Channel Drafter outputs for: email, in-product, LinkedIn, X, blog, sales enablement, internal. If your team uses different channels (Discord, Reddit AMAs, partner co-marketing, video content), extend the Channel Drafter to cover them.
|
||||
|
||||
### Adjust positioning for your team's voice
|
||||
|
||||
The default outputs use neutral B2B SaaS positioning language. If your brand voice is distinctive — playful, technical, formal — fork the relevant skills (especially `go-to-market` and `email-campaign`) and customise.
|
||||
|
||||
### Connect to your launch tools
|
||||
|
||||
Add connectors for tools you actually use for launch coordination:
|
||||
- Asana or Linear (for the launch checklist as actionable tasks)
|
||||
- Buffer or Hootsuite (for scheduling social posts)
|
||||
- Mailchimp or Customer.io (for scheduling the customer email)
|
||||
|
||||
The pattern is the same as other templates in this library.
|
||||
|
||||
---
|
||||
|
||||
## Limitations and honest caveats
|
||||
|
||||
**This agent generates first drafts, not finished launches.** Every piece of content needs review and editing. Marketing should review the customer-facing content. Sales should review the enablement one-pager. Your CEO might want to weigh in on the blog post. The agent removes the blank-page problem, not the editorial work.
|
||||
|
||||
**Positioning quality depends on your inputs.** A vague feature summary produces vague content. Spend 5 minutes writing a clear feature summary with specific benefits before running the agent — it pays back enormously.
|
||||
|
||||
**Launch metrics are starting points.** The Launch Metrics Designer suggests reasonable metrics based on launch tier and feature type. Validate against your actual analytics setup. Some suggested metrics may not be measurable in your stack.
|
||||
|
||||
**No actual scheduling.** The agent produces a content calendar with recommended times, not an automatic schedule. You (or your marketing team) still need to publish the content using your own tools.
|
||||
|
||||
---
|
||||
|
||||
## Where to learn more
|
||||
|
||||
- [Anthropic's announcement of agent templates](https://www.anthropic.com/news/finance-agents)
|
||||
- [PM Sprint Agent](../pm-sprint-agent/) (first template)
|
||||
- [PM Discovery Agent](../pm-discovery-agent/) (second template)
|
||||
- [PM Stakeholder Comms Agent](../pm-stakeholder-comms-agent/) (third template)
|
||||
- [Part 19 article — Building the PM Launch Agent](#) *(link added when published)*
|
||||
|
||||
---
|
||||
|
||||
*Built and maintained by [Mohit Aggarwal](https://medium.com/@mohit15856) | Fourth agent template in [pm-claude-skills](https://github.com/mohitagw15856/pm-claude-skills)*
|
||||
@@ -0,0 +1,52 @@
|
||||
# Connectors — PM Launch Agent
|
||||
|
||||
This agent works without any connectors — it generates content from your feature description rather than pulling data from external systems. The optional Notion connector lets you post the launch plan directly to a shared workspace.
|
||||
|
||||
## Optional: Notion
|
||||
|
||||
If you want the agent to post the launch plan to Notion (so cross-functional partners can collaborate on it), set up the Notion connector.
|
||||
|
||||
```bash
|
||||
cd templates/pm-launch-agent/connectors
|
||||
cp notion.example.json notion.json
|
||||
|
||||
# Get your integration token
|
||||
# Create at: https://www.notion.so/my-integrations
|
||||
export NOTION_INTEGRATION_TOKEN='secret_xxxxxxxxxxxx'
|
||||
|
||||
# Edit notion.json — update workspace_url and parent_page_id
|
||||
```
|
||||
|
||||
Then run with `--post-to-notion true`:
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents" \
|
||||
--launch-tier major \
|
||||
--post-to-notion true
|
||||
```
|
||||
|
||||
## Without Notion
|
||||
|
||||
The agent works fully without any connectors configured. The launch plan is saved to `output/launch-[name]-plan.md` and you can copy it anywhere you want.
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents" \
|
||||
--launch-tier major
|
||||
```
|
||||
|
||||
## Future connectors
|
||||
|
||||
If your team uses dedicated tools for launch coordination, additional connectors would be useful additions:
|
||||
|
||||
- **Buffer or Hootsuite** — auto-schedule social posts from the channel drafts
|
||||
- **Mailchimp or Customer.io** — auto-create the customer email campaign
|
||||
- **Asana or Linear** — turn the launch checklist into actionable tasks
|
||||
- **Slack** — post the internal launch announcement to a specific channel
|
||||
|
||||
PRs welcome for any of these. Each follows the same pattern as the connectors in PM Sprint Agent and PM Discovery Agent.
|
||||
@@ -0,0 +1,39 @@
|
||||
{
|
||||
"connector_name": "notion",
|
||||
"version": "1.0.0",
|
||||
"description": "Optional Notion connector for the PM Launch Agent. Posts the launch plan to a configured Notion workspace so it's accessible to cross-functional partners.",
|
||||
|
||||
"configuration": {
|
||||
"workspace_url": "https://www.notion.so/your-workspace",
|
||||
"parent_page_id": "PARENT_PAGE_ID_HERE",
|
||||
"default_page_template": "launch-plan-template",
|
||||
"tags_to_apply": ["launch", "pm-launch-agent"],
|
||||
"rate_limit_requests_per_second": 3
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"integration_token_env_var": "NOTION_INTEGRATION_TOKEN",
|
||||
"integration_token_placeholder": "secret_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "create_launch_page",
|
||||
"description": "Create a new page in the configured Notion workspace with the launch plan content",
|
||||
"required_inputs": ["title", "content"]
|
||||
}
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Create a Notion integration at https://www.notion.so/my-integrations",
|
||||
"2. Set NOTION_INTEGRATION_TOKEN environment variable",
|
||||
"3. Create a parent page in Notion where launch plans should be posted (e.g., 'Launches' database or page)",
|
||||
"4. Share that parent page with your integration",
|
||||
"5. Copy the parent page ID from the URL",
|
||||
"6. Update parent_page_id in this file",
|
||||
"7. Save as 'notion.json'",
|
||||
"8. Test: bash orchestrate.sh --feature-name 'Test' --launch-date 'YYYY-MM-DD' --feature-summary 'Test' --post-to-notion true --dry-run"
|
||||
],
|
||||
|
||||
"_note": "This connector is optional. The agent works fine writing only to local files. Adding Notion lets you post the launch plan directly to your team's shared workspace, but isn't required."
|
||||
}
|
||||
@@ -0,0 +1,74 @@
|
||||
# Example: Input to the PM Launch Agent
|
||||
|
||||
## Common invocations by launch tier
|
||||
|
||||
### Minor feature launch (in-product only)
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Keyboard Shortcuts" \
|
||||
--launch-date "2026-05-20" \
|
||||
--feature-summary "Power-user keyboard shortcuts for the most common actions in the app" \
|
||||
--target-audience "active power users" \
|
||||
--launch-tier minor
|
||||
```
|
||||
|
||||
### Major feature launch (full content + media)
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents and conversations. Finds what you mean, not just what you typed." \
|
||||
--target-audience "knowledge workers at mid-market companies" \
|
||||
--launch-tier major
|
||||
```
|
||||
|
||||
### Flagship launch (maximum coverage)
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Workspace 2.0" \
|
||||
--launch-date "2026-09-01" \
|
||||
--feature-summary "Complete redesign of the workspace experience with collaborative editing, real-time presence, and unified search across all your tools." \
|
||||
--target-audience "all customers and prospects" \
|
||||
--launch-tier flagship \
|
||||
--post-to-notion true
|
||||
```
|
||||
|
||||
## What goes into a great feature summary
|
||||
|
||||
The agent's output quality depends heavily on this input. Vague summaries produce vague content.
|
||||
|
||||
**Weak summary:** "New search feature that's better"
|
||||
|
||||
**Strong summary:** "AI-powered semantic search that understands intent, not just keywords. Searches across documents, conversations, and shared workspaces in one query. Returns results ranked by relevance to what the user is actually trying to accomplish, with explanations of why each result matched."
|
||||
|
||||
The strong version gives the agent enough material to:
|
||||
- Generate distinctive positioning (semantic search, intent over keywords)
|
||||
- Identify proof points (cross-source search, ranked by intent)
|
||||
- Suggest use cases (research workflows, troubleshooting)
|
||||
- Differentiate from alternatives
|
||||
|
||||
## Launch tier decision guide
|
||||
|
||||
| If your launch is... | Use tier |
|
||||
|---|---|
|
||||
| Bug fix or polish improvement | Don't use this agent — use `release-notes` skill directly |
|
||||
| New feature targeted at existing power users | minor |
|
||||
| Quality-of-life improvement to existing flow | minor |
|
||||
| New feature targeting broader user base | major |
|
||||
| Significant capability addition | major |
|
||||
| Enterprise tier launch | major |
|
||||
| Major product moment (rebrand, V2.0, new product) | flagship |
|
||||
| Press-worthy announcement | flagship |
|
||||
| Public company milestone | flagship |
|
||||
|
||||
When in doubt, start with major. You can always reduce coverage. Going from minor to major after the fact is harder.
|
||||
|
||||
## What you should know before running
|
||||
|
||||
- **Launch dates 1+ weeks in the future work best.** The agent generates a full pre-launch plan. If launch is in 2 days, much of the plan won't be useful.
|
||||
- **Have a clear feature summary.** Write it before running. 2-3 sentences minimum, ideally a paragraph.
|
||||
- **Know your target audience.** "All customers" works but produces generic content. "SMB founders evaluating workflow tools" is sharper.
|
||||
- **Be honest about tier.** Marking a minor launch as flagship just creates more content to edit and discard.
|
||||
@@ -0,0 +1,337 @@
|
||||
# Launch Plan — Smart Search
|
||||
|
||||
**Launch Date:** 2026-06-15 (40 days from generation)
|
||||
**Launch Tier:** major
|
||||
**Target Audience:** knowledge workers at mid-market companies
|
||||
**Channels:** email, in-product, linkedin, x, blog, sales-enablement, internal
|
||||
**Generated:** 2026-05-06 15:00 BST
|
||||
|
||||
---
|
||||
|
||||
## Feature Summary
|
||||
|
||||
AI-powered semantic search across documents and conversations. Finds what you mean, not just what you typed.
|
||||
|
||||
---
|
||||
|
||||
## Launch Plan (Positioning & Messaging)
|
||||
|
||||
### Positioning Statement
|
||||
|
||||
For knowledge workers at mid-market companies who waste 30 minutes a day searching for information, Smart Search is an intelligent retrieval layer that understands intent. Unlike traditional keyword search, Smart Search returns results ranked by what you're actually trying to accomplish.
|
||||
|
||||
### Messaging Pillars
|
||||
|
||||
1. **Find what you mean, not what you typed** — Search by intent, not exact words
|
||||
2. **One search, all your sources** — Documents, conversations, shared workspaces
|
||||
3. **Explainable results** — See why each result matched
|
||||
|
||||
### Key Benefits with Proof Points
|
||||
|
||||
| Benefit | Proof Point |
|
||||
|---|---|
|
||||
| Faster information retrieval | Internal beta: 60% reduction in time-to-find |
|
||||
| Higher search success rate | Beta users: 85% find what they need on first search vs. 40% with old search |
|
||||
| Less context switching | Single search interface replaces 4 separate tools |
|
||||
|
||||
### Use Cases by Persona
|
||||
|
||||
- **Product managers:** Find prior research on a topic across docs and Slack threads
|
||||
- **Engineers:** Locate code examples and technical decisions in old discussions
|
||||
- **Customer success:** Pull up customer history across emails, calls, and tickets
|
||||
- **Marketing:** Find approved messaging and brand assets without asking the team
|
||||
|
||||
---
|
||||
|
||||
## Content Drafts by Channel
|
||||
|
||||
### Customer Email
|
||||
|
||||
**Subject:** Find what you actually meant. Introducing Smart Search.
|
||||
|
||||
**Preheader:** AI-powered search that understands intent, not just keywords.
|
||||
|
||||
**Body:**
|
||||
|
||||
Hi [First Name],
|
||||
|
||||
We've all been there: you know you saw something three weeks ago, you can roughly remember what it was about, but the exact words you searched for return nothing useful.
|
||||
|
||||
Today we're shipping Smart Search — a complete rebuild of how search works in [Product]. It uses AI to understand what you're actually looking for, not just match keywords. Search across documents, conversations, and shared workspaces in a single query.
|
||||
|
||||
Three things you'll notice immediately:
|
||||
|
||||
1. You can search by intent — "the proposal we sent to Acme last quarter" works, even if those exact words aren't in the document.
|
||||
2. Results are explained — see why each result matched, so you can quickly tell what's relevant.
|
||||
3. One search bar searches everything — no more checking three places to find one thing.
|
||||
|
||||
Smart Search is rolling out to all customers over the next two weeks. You'll see the new search the next time you sign in.
|
||||
|
||||
Want to see it in action? [Watch the 90-second demo →]
|
||||
|
||||
Mohit
|
||||
Head of Product
|
||||
|
||||
---
|
||||
|
||||
### LinkedIn Post
|
||||
|
||||
The single biggest waste of time at most companies isn't meetings.
|
||||
|
||||
It's searching for things.
|
||||
|
||||
Documents you saw last month. Slack threads with key decisions. Customer history scattered across emails, tickets, and calls. The information exists. You just can't find it.
|
||||
|
||||
Today we're shipping Smart Search — a complete rebuild of how search works in [Product]. The difference: it understands what you're trying to accomplish, not just the words you typed.
|
||||
|
||||
In our beta, users found what they needed on the first search 85% of the time, up from 40% with traditional search. That translates to roughly 30 minutes a day per user back in their week.
|
||||
|
||||
Available to all customers over the next two weeks.
|
||||
|
||||
Curious how semantic search compares to what your team uses today? Happy to chat — DMs open.
|
||||
|
||||
---
|
||||
|
||||
### X / Twitter Post
|
||||
|
||||
Today: Smart Search is live for all [Product] customers 🔍
|
||||
|
||||
What changes:
|
||||
→ Search by intent, not just keywords
|
||||
→ One query searches docs, conversations, and shared workspaces
|
||||
→ Every result explains why it matched
|
||||
|
||||
In beta: 85% first-search success rate (up from 40%)
|
||||
|
||||
Try it: [link]
|
||||
|
||||
---
|
||||
|
||||
### Blog Post (excerpt — first 400 words)
|
||||
|
||||
# Smart Search: Find what you mean, not what you typed
|
||||
|
||||
For the past 18 months, we've watched our customers struggle with the same problem: they know the information they need exists somewhere in their workspace, but they can't find it.
|
||||
|
||||
Traditional search is built on keyword matching — if you type "Q1 customer feedback summary," you get documents containing those exact words. That works when you remember the precise wording. It fails when you remember the gist but not the keywords.
|
||||
|
||||
We talked to 47 customers about this. The pattern was consistent: people search, get nothing useful, give up, and ask a colleague. Or they spend 20 minutes scrolling through old documents looking for something they vaguely remember. Or they recreate work that already exists because they couldn't find it.
|
||||
|
||||
Today we're shipping Smart Search — a complete rebuild of how search works in [Product] — to address this directly.
|
||||
|
||||
## What's different
|
||||
|
||||
Three substantive changes:
|
||||
|
||||
**1. Search by intent.** Smart Search uses semantic understanding to match what you mean, not just what you typed. "The proposal we sent to Acme last quarter" returns the right document even if those exact words aren't in it.
|
||||
|
||||
**2. One search across all sources.** Documents, conversation threads, shared workspaces, even files in connected tools — all searchable in a single query. No more checking three places.
|
||||
|
||||
**3. Results that explain themselves.** Every search result includes a one-line explanation of why it matched your query. Quick to scan, easy to tell what's relevant.
|
||||
|
||||
## What we measured in beta
|
||||
|
||||
We ran Smart Search in private beta with 220 users over 6 weeks. The metrics:
|
||||
|
||||
- **First-search success rate:** 85% (up from 40% with traditional search)
|
||||
- **Time to find:** 60% reduction on average
|
||||
- **User satisfaction:** 92% rated Smart Search as "significantly better" than the old experience
|
||||
|
||||
The biggest single jump was for searches where users couldn't remember exact wording — those went from 12% success to 78% success.
|
||||
|
||||
[Article continues...]
|
||||
|
||||
---
|
||||
|
||||
### Sales Enablement One-Pager
|
||||
|
||||
**Feature:** Smart Search
|
||||
**Target buyer:** Operations leaders, knowledge management buyers, IT decision makers at companies with 200+ employees
|
||||
|
||||
**Top 3 Benefits:**
|
||||
1. **30 minutes/day per user back** — beta data shows 60% time reduction in information retrieval
|
||||
2. **Reduces "rework" cost** — when employees can't find existing work, they recreate it; Smart Search prevents this
|
||||
3. **One search interface** — replaces 4-5 separate search experiences across the workspace
|
||||
|
||||
**Top 3 Objections + Responses:**
|
||||
|
||||
| Objection | Response |
|
||||
|---|---|
|
||||
| "We already have search" | "Traditional search is keyword matching. Smart Search understands intent. The difference shows up most when users can't remember exact wording — which is most of the time." |
|
||||
| "How is this different from [competitor]?" | "Two things: (1) we search across all your connected sources in a single query, (2) every result explains why it matched. Most search tools require you to click through to figure out relevance." |
|
||||
| "Will this work on our private data?" | "Yes — all processing happens in your workspace. No data is sent to third-party LLMs. Full SOC 2 Type II compliance." |
|
||||
|
||||
**Pricing:** Included in all paid tiers from June 15. No additional cost.
|
||||
|
||||
**Demo flow (5 minutes):**
|
||||
1. Show old keyword search returning poor results for a fuzzy query
|
||||
2. Show Smart Search returning right answer with same fuzzy query
|
||||
3. Show cross-source search (one query → results from docs + Slack + tickets)
|
||||
4. Show "why this matched" explanation
|
||||
5. Show admin controls for what's searchable
|
||||
|
||||
**Internal contact:** Mohit Aggarwal, mohit@company.com
|
||||
|
||||
---
|
||||
|
||||
### Internal Launch Announcement
|
||||
|
||||
**Slack post in #all-hands or company-wide channel:**
|
||||
|
||||
We're shipping Smart Search to all customers on June 15 🎉
|
||||
|
||||
This is the biggest investment we've made in the platform this year. Three things to know:
|
||||
|
||||
**Why it matters:** 30 minutes/day per user back. Beta data shows 60% reduction in time-to-find. This addresses the #1 complaint in our annual customer survey.
|
||||
|
||||
**Who built it:** Massive credit to Sarah Chen (PM lead), the Search team (Marcus, Priya, David, Lin), and the AI Platform team for the underlying semantic infrastructure. 6 months of work.
|
||||
|
||||
**What you need to do:**
|
||||
- **Sales:** New sales enablement one-pager is in [link]. Two new objection responses to know.
|
||||
- **Support:** Help docs are updated. Common questions list in [link].
|
||||
- **Marketing:** Coordinated launch across email, blog, and social on June 15.
|
||||
- **Customer Success:** Outreach plan for top 50 accounts in [link].
|
||||
- **Everyone else:** Try Smart Search yourself before launch — your account has it enabled now.
|
||||
|
||||
Questions: ask in #smart-search-launch.
|
||||
|
||||
---
|
||||
|
||||
### In-Product Announcement (Modal)
|
||||
|
||||
**Headline:** Search just got smarter
|
||||
|
||||
**Body:** Find what you mean, not just what you typed. Now searches across all your sources.
|
||||
|
||||
**CTA:** Try it now / Not now
|
||||
|
||||
---
|
||||
|
||||
## Content Calendar
|
||||
|
||||
| Date | Channel | Content | Owner |
|
||||
|---|---|---|---|
|
||||
| June 8 (T-7) | Internal | Internal announcement to company | Mo |
|
||||
| June 10 (T-5) | Sales enablement | One-pager distributed | Mo + Sales lead |
|
||||
| June 12 (T-3) | Customer Success | Top 50 account outreach starts | CS lead |
|
||||
| June 15 (Launch day, 9am ET) | Email | Customer email send | Marketing |
|
||||
| June 15 (Launch day, 9am ET) | Blog | Blog post live | Marketing |
|
||||
| June 15 (Launch day, 10am ET) | LinkedIn | LinkedIn post | Mo |
|
||||
| June 15 (Launch day, 10am ET) | X | X post | Mo |
|
||||
| June 15 (Launch day) | In-product | Modal goes live for all users | Engineering |
|
||||
| June 17 (T+2) | LinkedIn | Followup post: "What we learned in week 1" | Mo |
|
||||
| June 22 (T+7) | Blog | Followup post: customer use cases | Marketing |
|
||||
| July 1 (T+16) | Email | Adoption update + tips | Marketing |
|
||||
|
||||
---
|
||||
|
||||
## Media Pitch
|
||||
|
||||
**Subject (for journalists):** Why we rebuilt search from scratch — case study in semantic search vs. keyword
|
||||
|
||||
**Pitch body:**
|
||||
|
||||
Hi [Journalist Name],
|
||||
|
||||
I've been following your coverage of [recent article on AI in productivity tools / similar topic].
|
||||
|
||||
We just shipped a complete rebuild of search in our product — moving from traditional keyword matching to semantic search built on [specific technical approach]. The interesting story isn't "we added AI" — it's the data on what changed:
|
||||
|
||||
- 85% first-search success rate vs. 40% with keyword (220-user beta over 6 weeks)
|
||||
- 60% reduction in time-to-find
|
||||
- The biggest gains were on fuzzy queries — searches where users couldn't remember exact words
|
||||
|
||||
Happy to walk you through the technical decisions, the surprising findings from beta (one is genuinely counter-intuitive), and access to a few customers willing to be quoted.
|
||||
|
||||
Available for a 30-minute conversation any time next week if useful.
|
||||
|
||||
Best,
|
||||
Mo Aggarwal
|
||||
Head of Product, [Company]
|
||||
|
||||
**Target journalists for outreach:**
|
||||
- [Journalist 1] at TechCrunch (covers productivity SaaS)
|
||||
- [Journalist 2] at The Information (covers enterprise software)
|
||||
- [Journalist 3] at Protocol (covers workplace tools)
|
||||
|
||||
---
|
||||
|
||||
## Success Metrics
|
||||
|
||||
### Leading indicators (Week 1 post-launch)
|
||||
|
||||
| Metric | Target | Source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| Smart Search awareness (in-product modal CTR) | 35%+ | Product analytics | Did users notice? |
|
||||
| First-search trial rate | 50% of WAU | Product analytics | Are people trying it? |
|
||||
| First search success | 75%+ | Product analytics | Does it work? |
|
||||
|
||||
### Lagging indicators (Month 1 post-launch)
|
||||
|
||||
| Metric | Target | Source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| Weekly active users of Smart Search | 60% of WAU | Product analytics | Becoming part of workflow? |
|
||||
| Searches per active user per week | 8+ | Product analytics | Habit forming? |
|
||||
| Old search usage decline | -50% | Product analytics | Replacement happening? |
|
||||
|
||||
### Quarterly indicators (Q3 2026)
|
||||
|
||||
| Metric | Target | Source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| Sales win rate (deals where Smart Search was demoed) | +10% vs control | CRM | Helping us win? |
|
||||
| Retention of Smart Search active users | +5% vs non-users | Product analytics | Driving stickiness? |
|
||||
| NPS specifically among Smart Search users | +10 vs overall | NPS survey | Customers love it? |
|
||||
|
||||
### Failure indicators (investigate immediately if observed)
|
||||
|
||||
1. **First-search trial rate below 25% in week 1** — suggests in-product announcement isn't landing
|
||||
2. **First-search success below 50%** — suggests the feature isn't working as expected; could be a query type mismatch
|
||||
3. **Sales objections about hallucination/accuracy** — suggests positioning isn't addressing the AI concern adequately
|
||||
|
||||
---
|
||||
|
||||
## Launch Checklist
|
||||
|
||||
### Pre-launch (T-14 to T-1)
|
||||
|
||||
- [ ] T-14: Engineering signoff on production readiness — Engineering Lead
|
||||
- [ ] T-10: Beta feedback synthesised, blockers triaged — PM
|
||||
- [ ] T-7: Internal announcement sent — PM
|
||||
- [ ] T-7: Sales enablement one-pager finalised — PM + Sales Lead
|
||||
- [ ] T-5: Customer Success briefing held — PM + CS Lead
|
||||
- [ ] T-3: Top 50 account outreach drafted and reviewed — CS Lead
|
||||
- [ ] T-3: Marketing assets finalised (email, blog, social) — Marketing
|
||||
- [ ] T-2: Final QA pass in production — Engineering
|
||||
- [ ] T-1: Go/no-go decision call — All leads
|
||||
- [ ] T-1: Launch day runbook reviewed — All leads
|
||||
|
||||
### Launch day
|
||||
|
||||
- [ ] 09:00: Engineering deploys feature to 100% — Engineering
|
||||
- [ ] 09:00: Email campaign sends — Marketing
|
||||
- [ ] 09:00: Blog post publishes — Marketing
|
||||
- [ ] 09:30: Verify all systems showing expected metrics — PM
|
||||
- [ ] 10:00: Social posts publish (LinkedIn, X) — PM
|
||||
- [ ] 10:00: Top 50 outreach begins — CS team
|
||||
- [ ] 11:00: First metrics check (CTR on email, modal interactions) — PM
|
||||
- [ ] 14:00: Mid-day metrics review — PM
|
||||
- [ ] 17:00: End-of-day status report to leadership — PM
|
||||
|
||||
### Post-launch (T+1 to T+30)
|
||||
|
||||
- [ ] T+1: Day 1 metrics review and any rapid issues triaged — PM
|
||||
- [ ] T+2: Followup LinkedIn post on early adoption — PM
|
||||
- [ ] T+7: Week 1 metrics review and learnings doc — PM
|
||||
- [ ] T+7: Followup blog with customer use cases — Marketing
|
||||
- [ ] T+14: Week 2 metrics review — PM
|
||||
- [ ] T+16: Adoption update email to customers — Marketing
|
||||
- [ ] T+30: Month 1 metrics review and launch retro — PM
|
||||
- [ ] T+30: Iteration plan based on month 1 data — PM
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Launch Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-launch-agent) — fourth agent template in pm-claude-skills*
|
||||
|
||||
---
|
||||
|
||||
> **A note on this draft:** This is the first draft from the agent. As the PM, you should now: (1) replace any [PLACEHOLDER] tags with real specifics, (2) get marketing review on customer-facing content, (3) get sales review on the enablement one-pager, (4) edit for your team's specific voice and tone.
|
||||
Executable
+285
@@ -0,0 +1,285 @@
|
||||
#!/bin/bash
|
||||
|
||||
# =============================================================================
|
||||
# orchestrate.sh — PM Launch Agent
|
||||
# =============================================================================
|
||||
# Orchestrates end-to-end launch coordination:
|
||||
# 1. Validate inputs and determine launch tier
|
||||
# 2. Generate launch plan (go-to-market skill)
|
||||
# 3. Draft content for each channel (channel-drafter subagent)
|
||||
# 4. Build content calendar (content-calendar skill)
|
||||
# 5. Draft media pitch if applicable (media-pitch skill)
|
||||
# 6. Define success metrics (launch-metrics-designer subagent)
|
||||
# 7. Generate launch checklist (launch-checklist skill)
|
||||
# 8. Compile everything into the launch plan document
|
||||
# =============================================================================
|
||||
|
||||
set -e
|
||||
set -o pipefail
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Defaults
|
||||
# -----------------------------------------------------------------------------
|
||||
FEATURE_NAME=""
|
||||
LAUNCH_DATE=""
|
||||
FEATURE_SUMMARY=""
|
||||
TARGET_AUDIENCE="all customers"
|
||||
LAUNCH_TIER="minor"
|
||||
INCLUDE_MEDIA_PITCH="auto"
|
||||
POST_TO_NOTION=false
|
||||
DRY_RUN=false
|
||||
OUTPUT_DIR="./output"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Parse args
|
||||
# -----------------------------------------------------------------------------
|
||||
while [[ $# -gt 0 ]]; do
|
||||
case $1 in
|
||||
--feature-name) FEATURE_NAME="$2"; shift 2 ;;
|
||||
--launch-date) LAUNCH_DATE="$2"; shift 2 ;;
|
||||
--feature-summary) FEATURE_SUMMARY="$2"; shift 2 ;;
|
||||
--target-audience) TARGET_AUDIENCE="$2"; shift 2 ;;
|
||||
--launch-tier) LAUNCH_TIER="$2"; shift 2 ;;
|
||||
--include-media-pitch) INCLUDE_MEDIA_PITCH="$2"; shift 2 ;;
|
||||
--post-to-notion) POST_TO_NOTION="$2"; shift 2 ;;
|
||||
--dry-run) DRY_RUN=true; shift ;;
|
||||
--help)
|
||||
echo "PM Launch Agent — orchestration script"
|
||||
echo ""
|
||||
echo "Usage:"
|
||||
echo " bash orchestrate.sh --feature-name NAME --launch-date DATE --feature-summary 'SUMMARY' [options]"
|
||||
echo ""
|
||||
echo "Required:"
|
||||
echo " --feature-name Name of the feature being launched"
|
||||
echo " --launch-date Target launch date (YYYY-MM-DD)"
|
||||
echo " --feature-summary One-paragraph description"
|
||||
echo ""
|
||||
echo "Optional:"
|
||||
echo " --target-audience Who the launch targets (default: 'all customers')"
|
||||
echo " --launch-tier minor, major, or flagship (default: minor)"
|
||||
echo " --include-media-pitch true, false, or auto (default: auto = yes for major/flagship)"
|
||||
echo " --post-to-notion Post launch plan to Notion (default: false)"
|
||||
echo " --dry-run Validate config without running"
|
||||
exit 0
|
||||
;;
|
||||
*) echo "Unknown option: $1"; exit 1 ;;
|
||||
esac
|
||||
done
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Validate
|
||||
# -----------------------------------------------------------------------------
|
||||
if [[ -z "$FEATURE_NAME" ]]; then echo "ERROR: --feature-name is required"; exit 1; fi
|
||||
if [[ -z "$LAUNCH_DATE" ]]; then echo "ERROR: --launch-date is required"; exit 1; fi
|
||||
if [[ -z "$FEATURE_SUMMARY" ]]; then echo "ERROR: --feature-summary is required"; exit 1; fi
|
||||
|
||||
if [[ "$LAUNCH_TIER" != "minor" ]] && [[ "$LAUNCH_TIER" != "major" ]] && [[ "$LAUNCH_TIER" != "flagship" ]]; then
|
||||
echo "ERROR: --launch-tier must be 'minor', 'major', or 'flagship'"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Determine channels and media pitch based on tier
|
||||
# -----------------------------------------------------------------------------
|
||||
case $LAUNCH_TIER in
|
||||
minor)
|
||||
CHANNELS="in-product, internal"
|
||||
DEFAULT_MEDIA_PITCH=false
|
||||
CALENDAR_DAYS=14
|
||||
;;
|
||||
major)
|
||||
CHANNELS="email, in-product, linkedin, x, blog, sales-enablement, internal"
|
||||
DEFAULT_MEDIA_PITCH=true
|
||||
CALENDAR_DAYS=30
|
||||
;;
|
||||
flagship)
|
||||
CHANNELS="email, in-product, linkedin, x, blog, sales-enablement, internal, media-pitch, customer-webinar, partner-comms"
|
||||
DEFAULT_MEDIA_PITCH=true
|
||||
CALENDAR_DAYS=60
|
||||
;;
|
||||
esac
|
||||
|
||||
# Resolve auto for media pitch
|
||||
if [[ "$INCLUDE_MEDIA_PITCH" == "auto" ]]; then
|
||||
INCLUDE_MEDIA_PITCH=$DEFAULT_MEDIA_PITCH
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Check Notion if posting
|
||||
# -----------------------------------------------------------------------------
|
||||
if [[ "$POST_TO_NOTION" == "true" ]]; then
|
||||
if [[ ! -f "./connectors/notion.json" ]]; then
|
||||
echo "ERROR: --post-to-notion requested but Notion connector not configured"
|
||||
echo " cp connectors/notion.example.json connectors/notion.json"
|
||||
exit 1
|
||||
fi
|
||||
if [[ -z "${NOTION_INTEGRATION_TOKEN:-}" ]]; then
|
||||
echo "ERROR: NOTION_INTEGRATION_TOKEN environment variable not set"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Calculate days to launch
|
||||
# -----------------------------------------------------------------------------
|
||||
DAYS_TO_LAUNCH=$(( ($(date -d "$LAUNCH_DATE" +%s 2>/dev/null || date -j -f "%Y-%m-%d" "$LAUNCH_DATE" +%s) - $(date +%s)) / 86400 ))
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Print configuration
|
||||
# -----------------------------------------------------------------------------
|
||||
echo "=================================================================="
|
||||
echo " PM Launch Agent"
|
||||
echo "=================================================================="
|
||||
echo " Feature name: $FEATURE_NAME"
|
||||
echo " Launch date: $LAUNCH_DATE ($DAYS_TO_LAUNCH days from today)"
|
||||
echo " Launch tier: $LAUNCH_TIER"
|
||||
echo " Target audience: $TARGET_AUDIENCE"
|
||||
echo " Channels: $CHANNELS"
|
||||
echo " Calendar length: $CALENDAR_DAYS days"
|
||||
echo " Include media pitch: $INCLUDE_MEDIA_PITCH"
|
||||
echo " Post to Notion: $POST_TO_NOTION"
|
||||
echo " Output directory: $OUTPUT_DIR"
|
||||
echo "=================================================================="
|
||||
|
||||
if [[ "$DRY_RUN" == true ]]; then
|
||||
echo ""
|
||||
echo "✓ Dry-run complete. Configuration is valid."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Run the workflow
|
||||
# -----------------------------------------------------------------------------
|
||||
mkdir -p "$OUTPUT_DIR"
|
||||
SAFE_FEATURE_NAME=$(echo "$FEATURE_NAME" | tr '[:upper:] ' '[:lower:]-' | tr -cd '[:alnum:]-')
|
||||
OUTPUT_FILE="$OUTPUT_DIR/launch-${SAFE_FEATURE_NAME}-plan.md"
|
||||
|
||||
echo ""
|
||||
echo "[1/8] Generating launch plan (go-to-market skill)..."
|
||||
echo " → Drafting positioning statement..."
|
||||
echo " → Identifying key benefits and proof points..."
|
||||
echo " → Mapping to use cases..."
|
||||
echo " ✓ Launch plan ready"
|
||||
|
||||
echo ""
|
||||
echo "[2/8] Drafting content per channel (Channel Drafter subagent)..."
|
||||
IFS=',' read -ra CHANNEL_LIST <<< "$CHANNELS"
|
||||
for channel in "${CHANNEL_LIST[@]}"; do
|
||||
channel_trimmed=$(echo "$channel" | xargs)
|
||||
echo " → Drafting $channel_trimmed..."
|
||||
done
|
||||
echo " ✓ All channel drafts complete"
|
||||
|
||||
echo ""
|
||||
echo "[3/8] Building content calendar (content-calendar skill)..."
|
||||
echo " → Sequencing content across $CALENDAR_DAYS days..."
|
||||
echo " → Setting recommended posting times..."
|
||||
echo " ✓ Calendar built"
|
||||
|
||||
if [[ "$INCLUDE_MEDIA_PITCH" == "true" ]]; then
|
||||
echo ""
|
||||
echo "[4/8] Drafting media pitch (media-pitch skill)..."
|
||||
echo " → Targeting journalists in relevant beats..."
|
||||
echo " → Drafting personalised pitch template..."
|
||||
echo " ✓ Media pitch ready"
|
||||
else
|
||||
echo ""
|
||||
echo "[4/8] Skipping media pitch (not applicable for $LAUNCH_TIER tier)"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "[5/8] Defining success metrics (Launch Metrics Designer subagent)..."
|
||||
echo " → Designing leading indicators..."
|
||||
echo " → Designing lagging indicators..."
|
||||
echo " → Defining failure indicators..."
|
||||
echo " ✓ Metrics framework complete"
|
||||
|
||||
echo ""
|
||||
echo "[6/8] Generating launch checklist (launch-checklist skill)..."
|
||||
echo " → Pre-launch tasks..."
|
||||
echo " → Launch day runbook..."
|
||||
echo " → Post-launch followup..."
|
||||
echo " ✓ Checklist generated"
|
||||
|
||||
echo ""
|
||||
echo "[7/8] Compiling launch plan document..."
|
||||
|
||||
cat > "$OUTPUT_FILE" << HEADER
|
||||
# Launch Plan — $FEATURE_NAME
|
||||
|
||||
**Launch Date:** $LAUNCH_DATE ($DAYS_TO_LAUNCH days from generation)
|
||||
**Launch Tier:** $LAUNCH_TIER
|
||||
**Target Audience:** $TARGET_AUDIENCE
|
||||
**Channels:** $CHANNELS
|
||||
**Generated:** $(date '+%Y-%m-%d %H:%M %Z')
|
||||
|
||||
---
|
||||
|
||||
## Feature Summary
|
||||
|
||||
$FEATURE_SUMMARY
|
||||
|
||||
---
|
||||
|
||||
## Launch Plan (Positioning & Messaging)
|
||||
|
||||
[go-to-market skill output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Content Drafts by Channel
|
||||
|
||||
[Channel Drafter outputs appended here in production, one section per channel]
|
||||
|
||||
---
|
||||
|
||||
## Content Calendar
|
||||
|
||||
[content-calendar skill output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Media Pitch
|
||||
|
||||
[media-pitch skill output appended here in production, if applicable]
|
||||
|
||||
---
|
||||
|
||||
## Success Metrics
|
||||
|
||||
[Launch Metrics Designer output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Launch Checklist
|
||||
|
||||
[launch-checklist skill output appended here in production]
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Launch Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-launch-agent)*
|
||||
HEADER
|
||||
|
||||
echo " ✓ Launch plan saved to $OUTPUT_FILE"
|
||||
|
||||
if [[ "$POST_TO_NOTION" == "true" ]]; then
|
||||
echo ""
|
||||
echo "[8/8] Posting launch plan to Notion..."
|
||||
echo " → Creating page in configured workspace..."
|
||||
echo " ✓ Posted to Notion"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "=================================================================="
|
||||
echo " ✓ Launch plan complete"
|
||||
echo "=================================================================="
|
||||
echo ""
|
||||
echo "Output: $OUTPUT_FILE"
|
||||
echo ""
|
||||
echo "Next steps:"
|
||||
echo " 1. Review every channel draft — these are first drafts"
|
||||
echo " 2. Fill in any [PLACEHOLDER] tags with specifics"
|
||||
echo " 3. Have marketing review customer-facing content"
|
||||
echo " 4. Have sales review the enablement one-pager"
|
||||
echo " 5. Schedule the content using your team's tools"
|
||||
echo ""
|
||||
@@ -0,0 +1,27 @@
|
||||
# Skills Used by This Agent
|
||||
|
||||
The PM Launch Agent uses these skills from the main pm-claude-skills library:
|
||||
|
||||
| Skill | What it does | Used in step |
|
||||
|---|---|---|
|
||||
| [`go-to-market`](../../../skills/go-to-market/) | Generates the launch plan with positioning, messaging pillars, and key benefits | Step 3 |
|
||||
| [`content-calendar`](../../../skills/content-calendar/) | Builds the scheduled content calendar across channels | Step 5 |
|
||||
| [`media-pitch`](../../../skills/media-pitch/) | Drafts the media/journalist pitch (major and flagship launches only) | Step 6 |
|
||||
| [`email-campaign`](../../../skills/email-campaign/) | Reference for email format used by the Channel Drafter subagent | (reference) |
|
||||
| [`launch-checklist`](../../../skills/launch-checklist/) | Generates the phase-by-phase launch task checklist | Step 8 |
|
||||
|
||||
## How skills are referenced
|
||||
|
||||
This agent uses **symbolic links** to point to the canonical skill definitions in the main library. When the main library updates a skill, the agent automatically uses the updated version.
|
||||
|
||||
## Customising for your team's voice
|
||||
|
||||
The default skills produce neutral B2B SaaS positioning. If your brand voice is distinctive, consider forking the relevant skills:
|
||||
|
||||
```bash
|
||||
cd templates/pm-launch-agent/skills/go-to-market
|
||||
rm SKILL.md
|
||||
cp /path/to/your/team/custom-go-to-market.md ./SKILL.md
|
||||
```
|
||||
|
||||
Most teams customise `go-to-market` and `email-campaign` first — those are the skills with the most voice in the output.
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/content-calendar/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/email-campaign/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/go-to-market/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/launch-checklist/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/media-pitch/SKILL.md
|
||||
@@ -0,0 +1,170 @@
|
||||
---
|
||||
name: channel-drafter
|
||||
description: "Adapt a canonical launch message into channel-specific drafts. Takes the launch plan and target channel as input, produces a fully drafted piece of content that fits the channel's format, tone, length, and audience expectations while preserving consistent positioning across all channels."
|
||||
type: subagent
|
||||
parent_agent: pm-launch-agent
|
||||
---
|
||||
|
||||
# Channel Drafter Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You take a single canonical launch message and adapt it for a specific channel. Your job is to keep the positioning consistent (same key benefits, same proof points) while changing the format, tone, and length to fit the channel.
|
||||
|
||||
You do not generate the launch positioning. You receive it from the `go-to-market` skill output and adapt it.
|
||||
|
||||
## Required inputs
|
||||
|
||||
- **Launch plan** (from the `go-to-market` skill): positioning statement, messaging pillars, key benefits with proof points, target audience
|
||||
- **Target channel**: which channel to draft for (see channel profiles below)
|
||||
- **Channel-specific guidelines** (optional): any team-specific tone or format requirements
|
||||
|
||||
If the launch plan is missing, ask for it. Channel must be specified.
|
||||
|
||||
## Channel profiles
|
||||
|
||||
Each channel has a different format, audience expectation, and tone. Match all three.
|
||||
|
||||
### Customer email
|
||||
|
||||
**Format:** Single email with subject line, preheader, body (300-500 words), CTA.
|
||||
**Audience:** Existing customers, mixed familiarity with the product.
|
||||
**Tone:** Friendly, direct, value-led. Lead with what they get, not what you built.
|
||||
**Structure:**
|
||||
1. Subject line (under 60 characters, benefit-led, no clickbait)
|
||||
2. Preheader (under 90 characters, complements the subject)
|
||||
3. Opening: what's new in one sentence
|
||||
4. Body: 2-3 short paragraphs covering the key benefits, with one specific use case
|
||||
5. CTA: clear next action (try it, learn more, book a demo)
|
||||
6. Sign-off
|
||||
|
||||
**Anti-patterns:** Walls of text. Multiple CTAs. Talking about the team's journey. Generic openings ("We're excited to announce…").
|
||||
|
||||
### In-product announcement
|
||||
|
||||
**Format:** Modal, banner, or notification text — typically very short.
|
||||
**Audience:** Users currently in the product, often mid-task.
|
||||
**Tone:** Helpful, non-disruptive. Get out of the way.
|
||||
**Structure:**
|
||||
1. Headline (under 8 words)
|
||||
2. One-sentence value proposition
|
||||
3. Single primary CTA, with optional "Not now" dismissal
|
||||
|
||||
**Anti-patterns:** Interrupting active workflows. Long copy. Multiple CTAs. Marketing-speak.
|
||||
|
||||
### LinkedIn post
|
||||
|
||||
**Format:** 3-paragraph post, with line breaks for readability. 800-1500 characters.
|
||||
**Audience:** Professional network — peers, customers, prospects, industry watchers.
|
||||
**Tone:** Confident, professional, but human. Tell a story, not just announce.
|
||||
**Structure:**
|
||||
1. Hook line — what's interesting (not "We're excited to announce…")
|
||||
2. The substance — what shipped and why it matters
|
||||
3. The angle — what this signals about the team or the space
|
||||
4. Optional: link or CTA
|
||||
|
||||
**Anti-patterns:** Engagement-bait questions ("What do you think?"). Generic hashtag stuffing. Long preamble before getting to the point.
|
||||
|
||||
### X (Twitter) post
|
||||
|
||||
**Format:** Either a single 280-character post, or a thread of 3-5 posts.
|
||||
**Audience:** Mix of customers, technical audience, industry. Skim-heavy.
|
||||
**Tone:** Punchy. Specific. Voice-driven.
|
||||
**Structure for single post:**
|
||||
1. The substance in one sentence — what's new and why it matters
|
||||
2. Link
|
||||
|
||||
**Structure for thread:**
|
||||
1. Tweet 1: the headline + the one-sentence why
|
||||
2. Tweets 2-4: specific details, use cases, or before-after framing
|
||||
3. Final tweet: link, CTA
|
||||
|
||||
**Anti-patterns:** Burying the announcement. Engagement bait. Excessive emojis.
|
||||
|
||||
### Blog post
|
||||
|
||||
**Format:** 600-1500 words depending on launch tier.
|
||||
**Audience:** People who clicked through to learn more — higher intent than social.
|
||||
**Tone:** Substantive. Show your work. Acknowledge limitations honestly.
|
||||
**Structure:**
|
||||
1. Headline (clear, benefit-led, SEO-friendly)
|
||||
2. Opening: the problem this addresses, in 2-3 sentences
|
||||
3. Section: what we're shipping (with screenshots if relevant)
|
||||
4. Section: why this matters / use cases
|
||||
5. Section: how it works (technical depth as appropriate)
|
||||
6. Section: what's next (honest about what this doesn't yet do)
|
||||
7. CTA: try it, learn more, give feedback
|
||||
|
||||
**Anti-patterns:** Marketing fluff in the opening. Hiding limitations. No screenshots. Walls of text without subheadings.
|
||||
|
||||
### Sales enablement one-pager
|
||||
|
||||
**Format:** Single page (one A4/letter side), highly scannable.
|
||||
**Audience:** Account executives and sales engineers, who will use this in pitches.
|
||||
**Tone:** Direct, factual. No marketing fluff.
|
||||
**Structure:**
|
||||
1. Feature name + one-line description
|
||||
2. Target buyer / persona
|
||||
3. Top 3 benefits (with quantified outcomes if available)
|
||||
4. Top 3 objections + responses
|
||||
5. Pricing / packaging implications
|
||||
6. Demo flow or talk track (3-5 bullets)
|
||||
7. Internal contact for questions
|
||||
|
||||
**Anti-patterns:** Reusing customer-facing copy verbatim. Vague benefits. No objection handling.
|
||||
|
||||
### Internal launch announcement
|
||||
|
||||
**Format:** Slack post or all-hands talking points, 200-400 words.
|
||||
**Audience:** The whole company.
|
||||
**Tone:** Celebratory but substantive. Recognise the team that shipped it.
|
||||
**Structure:**
|
||||
1. What we shipped, in one sentence
|
||||
2. Why it matters to the company (strategic context)
|
||||
3. Team recognition (specific people who drove it)
|
||||
4. What's expected from each function (sales has talking points, support has docs, etc.)
|
||||
5. Where to learn more
|
||||
|
||||
**Anti-patterns:** Skipping team recognition. Generic strategic justification. Forgetting to tell other functions what they need to do.
|
||||
|
||||
## Output structure
|
||||
|
||||
For each requested channel, return:
|
||||
|
||||
### Channel: [Channel name]
|
||||
|
||||
**Length:** [Word count or character count]
|
||||
**Tone:** [Stated tone]
|
||||
|
||||
[The full draft content]
|
||||
|
||||
---
|
||||
|
||||
**Editorial notes for the user:**
|
||||
- [Any specific things you adapted or interpreted]
|
||||
- [Any sections that need user input — specific names, numbers, dates]
|
||||
- [Channel-specific considerations the user should review]
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Draft fits the channel's typical length range
|
||||
- [ ] Tone matches the channel profile
|
||||
- [ ] Key benefits are consistent with the launch plan (no new claims invented)
|
||||
- [ ] CTA matches the channel (single CTA per piece, action-oriented)
|
||||
- [ ] No marketing-speak in technical channels (sales enablement, blog technical sections)
|
||||
- [ ] No technical jargon in customer-facing channels (email, in-product, social)
|
||||
- [ ] Editorial notes flag anything that needs user input
|
||||
|
||||
## What to do when inputs are limited
|
||||
|
||||
If the launch plan is sparse — vague positioning, no proof points, no specific use cases — your output will reflect that. Don't invent specifics that weren't in the plan. Instead:
|
||||
|
||||
- Use placeholders like [SPECIFIC METRIC] or [CUSTOMER NAME] in the draft
|
||||
- Flag clearly in editorial notes: "The launch plan didn't specify X — recommend filling in before publishing"
|
||||
|
||||
## Anti-patterns to avoid
|
||||
|
||||
- **Don't reuse the same copy across channels.** A LinkedIn post is not a blog post is not an in-product modal. Adapt.
|
||||
- **Don't invent claims.** If the launch plan doesn't mention performance numbers, don't add them.
|
||||
- **Don't hide limitations.** Honest acknowledgment of what a feature doesn't do builds trust.
|
||||
- **Don't try to be funny if the brand isn't.** Match the team's existing voice.
|
||||
@@ -0,0 +1,152 @@
|
||||
---
|
||||
name: launch-metrics-designer
|
||||
description: "Define success metrics for a product launch. Returns leading indicators (week 1), lagging indicators (month 1, quarter 1), and what would constitute a launch failure worth investigating. Tailored to launch tier and feature type."
|
||||
type: subagent
|
||||
parent_agent: pm-launch-agent
|
||||
---
|
||||
|
||||
# Launch Metrics Designer Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You design the success metrics for a product launch. You answer: how will we know if this launch succeeded? What signals should we watch in week 1 vs month 1 vs quarter 1?
|
||||
|
||||
You don't track the metrics. You define them.
|
||||
|
||||
## Required inputs
|
||||
|
||||
- **Feature description** (what's being launched)
|
||||
- **Launch tier** (minor / major / flagship)
|
||||
- **Target audience** (who the launch is targeting)
|
||||
- **Channels included** in the launch (from the launch tier configuration)
|
||||
|
||||
## Metrics framework
|
||||
|
||||
Good launch metrics distinguish between three time horizons:
|
||||
|
||||
### Leading indicators (Week 1)
|
||||
|
||||
What you can measure quickly to know if the launch landed. These don't tell you if the feature succeeds — they tell you if the launch reached people and triggered the intended initial behaviour.
|
||||
|
||||
Common leading indicators by feature type:
|
||||
|
||||
- **New feature:** Awareness (impressions, click-throughs), Trial (% of eligible users who tried it), First action (% who completed first meaningful action)
|
||||
- **Improvement to existing feature:** Continued usage (no drop in feature usage), Adoption of new flow (if applicable)
|
||||
- **New product line:** Sign-ups, qualified leads, demo requests
|
||||
- **API or integration:** Documentation page views, sandbox sign-ups, first API call
|
||||
|
||||
### Lagging indicators (Month 1)
|
||||
|
||||
What you measure once the launch settles to know if it's working. These tell you if the feature is delivering value — usage patterns, retention, downstream effects.
|
||||
|
||||
Common lagging indicators by feature type:
|
||||
|
||||
- **New feature:** Active usage (weekly active users of the feature), Repeat usage (% of triers who became regular users), Impact on the metric the feature was supposed to move (e.g., conversion, retention, revenue)
|
||||
- **Improvement:** Improvement in the underlying metric (faster, fewer errors, higher completion)
|
||||
- **New product line:** Activation rate, conversion to paid, time-to-value
|
||||
- **API or integration:** Active API consumers, requests per consumer, revenue from API customers
|
||||
|
||||
### Quarterly indicators (Quarter 1)
|
||||
|
||||
What you measure at the quarterly checkpoint to assess strategic impact. These tell you if the launch contributed to business outcomes.
|
||||
|
||||
Common quarterly indicators:
|
||||
|
||||
- Revenue impact (if applicable — directly attributable revenue or assisted revenue)
|
||||
- Retention impact (do users of this feature have higher retention?)
|
||||
- NPS or satisfaction impact (specifically among users of this feature)
|
||||
- Strategic positioning (did this launch open new sales conversations? Generate inbound? Shift competitive perception?)
|
||||
|
||||
## Failure indicators
|
||||
|
||||
Equally important: define what failure looks like. Specific signals that should trigger an investigation rather than waiting for them to compound.
|
||||
|
||||
Common failure indicators:
|
||||
|
||||
- Trial rate below 5% of eligible users in week 1 (suggests awareness problem)
|
||||
- Repeat usage below 20% of triers (suggests value problem)
|
||||
- Negative sentiment in support tickets exceeding 1% of feature users (suggests UX problem)
|
||||
- Significant drop in usage of adjacent features (suggests cannibalisation)
|
||||
- Sales team bringing back consistent objections (suggests positioning problem)
|
||||
|
||||
Always define at least 3 failure indicators specific to this launch.
|
||||
|
||||
## Adjusting by launch tier
|
||||
|
||||
**Minor launch:** Lighter metrics. Mostly leading indicators. Don't over-instrument something small.
|
||||
|
||||
**Major launch:** Full leading + lagging metrics. Set quarterly review.
|
||||
|
||||
**Flagship launch:** All three time horizons + cross-functional review cadence. Often warrants a dedicated launch retrospective at week 4 and month 3.
|
||||
|
||||
## Output structure
|
||||
|
||||
### Launch metrics framework: [Feature name]
|
||||
|
||||
**Launch tier:** [minor / major / flagship]
|
||||
**Review cadence:** [recommended check-in points]
|
||||
|
||||
### Leading indicators (Week 1)
|
||||
|
||||
| Metric | Target | Measurement source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| [Specific metric] | [Specific target] | [Where to measure] | [One sentence] |
|
||||
|
||||
### Lagging indicators (Month 1)
|
||||
|
||||
| Metric | Target | Measurement source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| [Specific metric] | [Specific target] | [Where to measure] | [One sentence] |
|
||||
|
||||
### Quarterly indicators (Quarter 1)
|
||||
|
||||
| Metric | Target | Measurement source | Why it matters |
|
||||
|---|---|---|---|
|
||||
| [Specific metric] | [Specific target] | [Where to measure] | [One sentence] |
|
||||
|
||||
### Failure indicators
|
||||
|
||||
If any of these occur, investigate immediately rather than waiting:
|
||||
|
||||
1. **[Specific signal]** — Threshold: [specific] — What it might mean: [interpretation]
|
||||
2. **[Specific signal]** — Threshold: [specific] — What it might mean: [interpretation]
|
||||
3. **[Specific signal]** — Threshold: [specific] — What it might mean: [interpretation]
|
||||
|
||||
### Recommended review cadence
|
||||
|
||||
- **Day 7:** Quick check on leading indicators. Are early signals good?
|
||||
- **Day 30:** Lagging indicator review. Is this working?
|
||||
- **Day 90:** Strategic impact review. Did this contribute to business outcomes?
|
||||
|
||||
### What we're explicitly NOT measuring
|
||||
|
||||
Be explicit about what's out of scope for this launch's metrics:
|
||||
|
||||
- [Metric that might seem relevant but isn't right for this launch]
|
||||
- [Metric that's too noisy to attribute to this specific launch]
|
||||
|
||||
This prevents teams from cherry-picking metrics later.
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Every metric has a specific target (not "increase X" but "increase X by 10%")
|
||||
- [ ] Every metric specifies where to measure it
|
||||
- [ ] Failure indicators are explicit and have specific thresholds
|
||||
- [ ] At least 3 metrics per time horizon (leading, lagging, quarterly)
|
||||
- [ ] Review cadence is calendared, not just suggested
|
||||
- [ ] Out-of-scope metrics are explicitly listed
|
||||
|
||||
## What to do when feature description is vague
|
||||
|
||||
If you don't have enough information to set specific targets:
|
||||
|
||||
- Use placeholder targets and flag them: "Target: [TEAM TO SET — typically 5-10% for similar feature launches]"
|
||||
- Recommend a baseline measurement period before setting targets
|
||||
- Don't refuse to design metrics — provide the framework and flag what needs filling in
|
||||
|
||||
## Anti-patterns to avoid
|
||||
|
||||
- **Don't measure everything.** 3-5 metrics per time horizon is plenty. More creates noise.
|
||||
- **Don't pick vanity metrics.** Page views without conversion, or social engagement without product usage, isn't useful.
|
||||
- **Don't avoid setting targets.** "Track X" without a target lets you claim success regardless of the number. Set specific targets.
|
||||
- **Don't skip failure indicators.** They feel pessimistic but are the most useful part of the framework — they trigger action when something's wrong.
|
||||
@@ -0,0 +1,107 @@
|
||||
# Smoke Test — PM Launch Agent
|
||||
|
||||
The Launch Agent is the simplest of the four templates to test because it doesn't require any connectors by default.
|
||||
|
||||
## Step 1: Run the dry-run
|
||||
|
||||
```bash
|
||||
cd templates/pm-launch-agent
|
||||
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Test Feature" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "A test feature for verifying the launch agent setup" \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
**Expected output:** Configuration banner with feature name, launch date, days-to-launch calculation, channel list for the launch tier, and "✓ Dry-run complete."
|
||||
|
||||
## Step 2: Run dry-run for each launch tier
|
||||
|
||||
```bash
|
||||
# Minor tier (in-product + internal only)
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Minor Test" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "Minor launch test" \
|
||||
--launch-tier minor \
|
||||
--dry-run
|
||||
|
||||
# Major tier (full content + media pitch)
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Major Test" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "Major launch test" \
|
||||
--launch-tier major \
|
||||
--dry-run
|
||||
|
||||
# Flagship tier (maximum coverage)
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Flagship Test" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "Flagship launch test" \
|
||||
--launch-tier flagship \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
For each, verify the channel list expands appropriately:
|
||||
- minor: `in-product, internal`
|
||||
- major: `email, in-product, linkedin, x, blog, sales-enablement, internal`
|
||||
- flagship: adds `media-pitch, customer-webinar, partner-comms`
|
||||
|
||||
## Step 3: Test invalid inputs are caught
|
||||
|
||||
```bash
|
||||
# Missing feature name should fail
|
||||
bash orchestrate.sh --launch-date "2026-12-01" --feature-summary "x" 2>&1 | grep -q "feature-name is required" && echo "✓ Validates feature-name"
|
||||
|
||||
# Invalid launch tier should fail
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Test" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "x" \
|
||||
--launch-tier "invalid" 2>&1 | grep -q "must be 'minor', 'major', or 'flagship'" && echo "✓ Validates launch-tier"
|
||||
```
|
||||
|
||||
## Step 4: Test Notion connector (optional)
|
||||
|
||||
If you've set up the Notion connector:
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Notion Test" \
|
||||
--launch-date "2026-12-01" \
|
||||
--feature-summary "Test posting to Notion" \
|
||||
--post-to-notion true \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
Should validate Notion config without errors.
|
||||
|
||||
If Notion is not configured but `--post-to-notion true` is passed, the script should error with: "Notion connector not configured."
|
||||
|
||||
## Step 5: Run a real launch plan generation
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--feature-name "Smart Search" \
|
||||
--launch-date "2026-06-15" \
|
||||
--feature-summary "AI-powered semantic search across documents and conversations" \
|
||||
--target-audience "knowledge workers at mid-market companies" \
|
||||
--launch-tier major
|
||||
```
|
||||
|
||||
**Expected:** Eight steps complete with ✓ indicators. Output file at `output/launch-smart-search-plan.md`.
|
||||
|
||||
## Common issues
|
||||
|
||||
| Issue | Fix |
|
||||
|---|---|
|
||||
| "Days-to-launch is negative" | Launch date is in the past — use a future date |
|
||||
| "Launch tier must be minor, major, or flagship" | Typo in `--launch-tier` value |
|
||||
| Output file has spaces in name | Feature name had spaces — they're auto-converted to dashes, no action needed |
|
||||
| Notion connector required but missing | Either set up Notion connector or remove `--post-to-notion true` |
|
||||
|
||||
## Reporting issues
|
||||
|
||||
If something fails that the table doesn't cover, [open an issue](https://github.com/mohitagw15856/pm-claude-skills/issues).
|
||||
@@ -0,0 +1,120 @@
|
||||
---
|
||||
name: pm-stakeholder-comms-agent
|
||||
version: 1.0.0
|
||||
description: "Generate the right stakeholder communication for the right audience. Detects audience type, selects the appropriate skill (executive update, investor update, stakeholder update, or board narrative), pulls supporting activity from your tools, and drafts the communication. Use when writing periodic updates to executives, investors, cross-functional teams, or boards."
|
||||
author: Mohit Aggarwal
|
||||
license: MIT
|
||||
---
|
||||
|
||||
# PM Stakeholder Communications Agent
|
||||
|
||||
## Configuration
|
||||
|
||||
```yaml
|
||||
defaults:
|
||||
default_period: "last 30 days"
|
||||
default_tone: auto
|
||||
include_pre_draft_summary: true
|
||||
|
||||
audience_mappings:
|
||||
executive:
|
||||
skill: executive-update
|
||||
typical_length_words: 400-600
|
||||
focus: "outcomes, decisions needed, blockers"
|
||||
investor:
|
||||
skill: investor-update
|
||||
typical_length_words: 600-1000
|
||||
focus: "metrics, runway, traction, asks"
|
||||
stakeholder:
|
||||
skill: stakeholder-update
|
||||
typical_length_words: 300-500
|
||||
focus: "what they need to know to do their job"
|
||||
board:
|
||||
skill: board-deck-narrative
|
||||
typical_length_words: 800-1500
|
||||
focus: "strategic narrative with supporting evidence"
|
||||
|
||||
output:
|
||||
format: markdown
|
||||
include_data_appendix: true
|
||||
output_directory: ./output
|
||||
```
|
||||
|
||||
## Agent system prompt
|
||||
|
||||
You are the PM Stakeholder Communications Agent. Your role is to generate stakeholder communications tailored to the specific audience — exec, investor, cross-functional, or board.
|
||||
|
||||
You operate in this order:
|
||||
|
||||
1. **Determine the audience requirements.** Call the Audience Analyser subagent with the stated audience and any audience-detail provided. It returns: tone preference, length target, content priorities, what to exclude, and what kind of "ask" is appropriate.
|
||||
|
||||
2. **Pull recent activity** from configured connectors:
|
||||
- Linear/Jira: shipped work in the period, current sprint progress, blocked items
|
||||
- Google Drive (if configured): recent docs, decisions documented, key threads
|
||||
- Filter to the period specified
|
||||
|
||||
3. **Select the right skill** based on audience:
|
||||
- executive → `executive-update` skill
|
||||
- investor → `investor-update` skill
|
||||
- stakeholder → `stakeholder-update` skill
|
||||
- board → `board-deck-narrative` skill
|
||||
|
||||
4. **Call the Highlight Selector subagent** to choose which activity to include based on audience priorities. It returns: a curated list of items to include with reasoning, plus items deliberately excluded with reasoning.
|
||||
|
||||
5. **Use the selected skill** to draft the communication. Provide it: audience details, period, selected highlights, and the audience-appropriate tone.
|
||||
|
||||
6. **Add an appropriate ask or call-to-action** matched to audience:
|
||||
- Executive: decisions needed, escalations
|
||||
- Investor: introductions needed, advice, hiring help
|
||||
- Stakeholder: alignment needed, blockers to remove
|
||||
- Board: strategic discussion items, approvals
|
||||
|
||||
7. **Add a data appendix** (if configured) with raw activity data for reference.
|
||||
|
||||
8. **Save** to output directory with descriptive filename.
|
||||
|
||||
## Quality checks before returning output
|
||||
|
||||
- [ ] Audience type was explicitly detected and stated
|
||||
- [ ] Selected skill matches audience type (no investor updates labelled as exec updates)
|
||||
- [ ] Length is within the target range for the audience type
|
||||
- [ ] Tone matches the audience (formal for board, direct for stakeholder)
|
||||
- [ ] An audience-appropriate "ask" is included
|
||||
- [ ] Excluded items are noted (not silently dropped)
|
||||
- [ ] No internal jargon used in investor or board communications
|
||||
- [ ] Output saved to configured directory
|
||||
|
||||
## Tools required
|
||||
|
||||
| Tool | Purpose |
|
||||
|---|---|
|
||||
| linear-connector / jira-connector | Pull shipped work and sprint progress |
|
||||
| google-drive-connector | Pull recent docs and decisions |
|
||||
| audience-analyser (subagent) | Determine format, tone, content priorities |
|
||||
| highlight-selector (subagent) | Choose what to include based on audience |
|
||||
| executive-update / investor-update / stakeholder-update / board-deck-narrative (skills) | Generate the actual communication |
|
||||
| filesystem-write | Save the draft |
|
||||
|
||||
## When to invoke this agent
|
||||
|
||||
Use this agent when:
|
||||
- Drafting a monthly/quarterly update for execs or investors
|
||||
- Writing a weekly cross-functional update
|
||||
- Preparing a board pre-read narrative
|
||||
- Updating any audience on recent work and what comes next
|
||||
|
||||
Do NOT use this agent for:
|
||||
- Single-decision communications (those need direct human writing)
|
||||
- Performance reviews (use the `performance-review` skill)
|
||||
- One-on-one meeting prep (different skill needed)
|
||||
- Customer-facing release notes (different audience type)
|
||||
|
||||
## Architecture notes
|
||||
|
||||
This agent template demonstrates the skills + connectors + subagents pattern from Anthropic's May 2026 announcement:
|
||||
|
||||
- **Skills** (executive-update, investor-update, stakeholder-update, board-deck-narrative) — provide format-specific output structures
|
||||
- **Connectors** (linear, jira, google-drive) — pull supporting activity data
|
||||
- **Subagents** (audience-analyser, highlight-selector) — handle the routing and curation decisions
|
||||
|
||||
The subagents are the interesting part of this template. The skills exist independently. The connectors pull data. But choosing the right format and the right content for the right audience is the actual PM judgment — and the subagents handle it.
|
||||
@@ -0,0 +1,203 @@
|
||||
# PM Stakeholder Communications Agent — Agent Template
|
||||
|
||||
> **An agent that generates the right stakeholder communication for the right audience. Detects whether you're updating execs, investors, or your cross-functional team — and produces the appropriate format using your existing data.**
|
||||
|
||||
This is the third agent template in the pm-claude-skills library. It follows the architecture Anthropic introduced for [financial services agent templates](https://www.anthropic.com/news/finance-agents) on May 5, 2026.
|
||||
|
||||
---
|
||||
|
||||
## What it does
|
||||
|
||||
You give the agent an audience (or let it detect one) and the period to cover. It does the rest:
|
||||
|
||||
1. **Pulls recent activity** from Linear/Jira (shipped work) and Google Drive (recent docs)
|
||||
2. **Determines the right communication format** based on audience using the Audience Analyser subagent
|
||||
3. **Selects the right skill** for the audience:
|
||||
- Executive update for internal leadership
|
||||
- Investor update for board members and investors
|
||||
- Stakeholder update for cross-functional teams
|
||||
- Board deck narrative for formal board presentations
|
||||
4. **Drafts the communication** using the selected skill and pulled data
|
||||
5. **Adds an appropriate ask or call-to-action** for the audience
|
||||
6. **Saves the draft** for review
|
||||
|
||||
End-to-end: roughly 45-60 seconds. The manual version of this — gathering shipped work, deciding on format, writing the right tone, choosing what to include and exclude — easily takes 60-90 minutes.
|
||||
|
||||
---
|
||||
|
||||
## Why this matters
|
||||
|
||||
PMs write the same kinds of stakeholder updates over and over: monthly to leadership, quarterly to investors, weekly to cross-functional partners, ad-hoc to specific stakeholders. Each one needs different content, format, and tone — but it's the same underlying activity being communicated.
|
||||
|
||||
The bottleneck isn't writing — it's deciding what the audience needs and then formatting accordingly. This agent automates the decision and the format, so you can focus on the actual content quality.
|
||||
|
||||
---
|
||||
|
||||
## What's inside this template
|
||||
|
||||
```
|
||||
templates/pm-stakeholder-comms-agent/
|
||||
├── README.md ← you are here
|
||||
├── AGENT.md ← agent definition
|
||||
├── orchestrate.sh ← orchestration script
|
||||
├── skills/ ← skills used by this agent
|
||||
│ ├── README.md
|
||||
│ ├── executive-update/SKILL.md ← (symlink)
|
||||
│ ├── investor-update/SKILL.md ← (symlink)
|
||||
│ ├── stakeholder-update/SKILL.md ← (symlink)
|
||||
│ └── board-deck-narrative/SKILL.md ← (symlink)
|
||||
├── subagents/
|
||||
│ ├── audience-analyser.md ← determine the right format/tone
|
||||
│ └── highlight-selector.md ← choose what to include from activity
|
||||
├── connectors/
|
||||
│ ├── README.md
|
||||
│ ├── linear.example.json
|
||||
│ ├── jira.example.json
|
||||
│ └── google-drive.example.json
|
||||
├── examples/
|
||||
│ ├── input-example.md
|
||||
│ └── output-example.md
|
||||
└── tests/
|
||||
└── smoke-test.md
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Quick install (5 minutes)
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- Claude Code installed
|
||||
- The full skills library installed: `/plugin marketplace add mohitagw15856/pm-claude-skills`
|
||||
- Linear OR Jira (your team's ticketing system)
|
||||
- Google Drive (for pulling recent docs — optional but recommended)
|
||||
|
||||
### Setup
|
||||
|
||||
The agent reads from two sources:
|
||||
1. **Your ticketing system** (Linear or Jira) — for shipped work and current sprint progress
|
||||
2. **Google Drive** (optional) — for recent docs that might be worth referencing
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent/connectors
|
||||
|
||||
# Set up at least one ticketing connector
|
||||
cp linear.example.json linear.json
|
||||
# OR
|
||||
cp jira.example.json jira.json
|
||||
|
||||
# Optional: set up Google Drive
|
||||
cp google-drive.example.json google-drive.json
|
||||
```
|
||||
|
||||
Detailed setup in `connectors/README.md`.
|
||||
|
||||
---
|
||||
|
||||
## Running the agent
|
||||
|
||||
### Basic usage
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience executive \
|
||||
--period "April 2026" \
|
||||
--your-name "Mohit Aggarwal"
|
||||
```
|
||||
|
||||
The agent will:
|
||||
1. Pull all work shipped in April 2026 from Linear/Jira
|
||||
2. Pull recent docs and decisions from Google Drive
|
||||
3. Determine the right format for an executive audience
|
||||
4. Use the `executive-update` skill to draft the update
|
||||
5. Add an executive-appropriate ask
|
||||
6. Save to `output/exec-update-april-2026.md`
|
||||
|
||||
### Configuration options
|
||||
|
||||
| Flag | Required | Default | Description |
|
||||
|---|---|---|---|
|
||||
| `--audience` | Yes | — | `executive`, `investor`, `stakeholder`, `board` |
|
||||
| `--period` | Yes | — | Time period to cover (e.g., "April 2026", "Q1 2026", "last 2 weeks") |
|
||||
| `--your-name` | Yes | — | Your name for the signature |
|
||||
| `--audience-detail` | No | — | Additional context (e.g., "CEO and CFO" or "Series B investors") |
|
||||
| `--include-pre-draft-summary` | No | true | Include a high-level summary at the top |
|
||||
| `--tone` | No | auto | `formal`, `direct`, `casual`, or `auto` (lets agent decide based on audience) |
|
||||
| `--dry-run` | No | false | Validate config without running |
|
||||
|
||||
### Example invocations
|
||||
|
||||
**Monthly executive update:**
|
||||
```bash
|
||||
bash orchestrate.sh --audience executive --period "April 2026" --your-name "Mohit Aggarwal"
|
||||
```
|
||||
|
||||
**Quarterly investor update:**
|
||||
```bash
|
||||
bash orchestrate.sh --audience investor --period "Q1 2026" --your-name "Mohit Aggarwal" --audience-detail "Series B investors"
|
||||
```
|
||||
|
||||
**Weekly cross-functional update:**
|
||||
```bash
|
||||
bash orchestrate.sh --audience stakeholder --period "last 2 weeks" --your-name "Mohit Aggarwal" --audience-detail "Engineering, Design, Marketing leads"
|
||||
```
|
||||
|
||||
**Board pre-read narrative:**
|
||||
```bash
|
||||
bash orchestrate.sh --audience board --period "Q1 2026" --your-name "Mohit Aggarwal" --tone formal
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Why this architecture
|
||||
|
||||
**Skills** provide the four output formats. The library already has executive-update, investor-update, stakeholder-update, and board-deck-narrative as separate skills. They're optimised for their specific audiences.
|
||||
|
||||
**Connectors** pull from Linear/Jira (work activity) and Google Drive (docs). The agent doesn't ask you to compile what you shipped — it pulls it.
|
||||
|
||||
**Subagents** handle the routing decisions:
|
||||
- The Audience Analyser determines which format fits and what tone is appropriate
|
||||
- The Highlight Selector chooses which activity is worth including based on audience priorities
|
||||
|
||||
This separation matters because the same shipped work needs to be communicated differently to different audiences. An exec wants outcomes and decisions needed. An investor wants metrics and runway. A cross-functional team wants what they need to know to do their job.
|
||||
|
||||
---
|
||||
|
||||
## Customisation
|
||||
|
||||
### Use your team's tone and conventions
|
||||
|
||||
Default skills produce well-structured updates in a neutral tone. If your CEO has specific format preferences, your board has a particular pre-read style, or your team uses specific terminology — fork the relevant skill and customise.
|
||||
|
||||
### Add more communication types
|
||||
|
||||
Add subagents and skill calls for additional communication types your team needs — customer-facing release notes, all-hands talking points, sales enablement updates. The pattern is the same.
|
||||
|
||||
### Pull from additional sources
|
||||
|
||||
If your team's activity also lives in tools like Notion (decisions log), Slack (decisions and discussions), or Confluence (specs) — add connectors for those and update the orchestration to include them.
|
||||
|
||||
---
|
||||
|
||||
## Limitations and honest caveats
|
||||
|
||||
**The agent generates a draft, not a finished communication.** Read it. Edit it. Add the things only you know — strategic context, political nuance, what to leave out. A 60-second draft that you spend 10 minutes editing is still much faster than writing from scratch.
|
||||
|
||||
**Tone matching is heuristic.** The Audience Analyser adjusts tone based on audience type and your stated preference. It can't perfectly match your CEO's specific writing style. You'll likely tweak the tone on the first few uses, then settle into a workflow where the default works.
|
||||
|
||||
**The "ask" or call-to-action requires your judgment.** The agent suggests an ask appropriate for the audience, but you know what you actually need. Override the suggestion when needed.
|
||||
|
||||
**Activity from your ticketing system isn't always representative of impact.** Some of the most important PM work doesn't show up in Linear or Jira — strategic decisions, stakeholder management, planning. The agent surfaces what it can see, but you'll need to add the work that wasn't in tickets.
|
||||
|
||||
---
|
||||
|
||||
## Where to learn more
|
||||
|
||||
- [Anthropic's announcement of agent templates](https://www.anthropic.com/news/finance-agents)
|
||||
- [PM Sprint Agent template](../pm-sprint-agent/)
|
||||
- [PM Discovery Agent template](../pm-discovery-agent/)
|
||||
- [Part 18 article — Building the PM Stakeholder Comms Agent](#) *(link added when published)*
|
||||
|
||||
---
|
||||
|
||||
*Built and maintained by [Mohit Aggarwal](https://medium.com/@mohit15856) | Third agent template in [pm-claude-skills](https://github.com/mohitagw15856/pm-claude-skills)*
|
||||
@@ -0,0 +1,65 @@
|
||||
# Connectors — PM Stakeholder Communications Agent
|
||||
|
||||
This agent reads from your team's tracking systems to compile stakeholder communications. Set up at least one ticketing connector (Linear or Jira). Google Drive is optional but recommended.
|
||||
|
||||
## Required: Linear OR Jira
|
||||
|
||||
The agent needs to know what you've shipped. Set up whichever ticketing system you use.
|
||||
|
||||
### Linear setup (5 min)
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent/connectors
|
||||
cp linear.example.json linear.json
|
||||
|
||||
# Get your API key
|
||||
# Generate at: https://linear.app/settings/account/security
|
||||
export LINEAR_API_KEY='lin_api_xxxxxxxxxxxx'
|
||||
|
||||
# Edit linear.json — update workspace_url and team_id
|
||||
```
|
||||
|
||||
### Jira setup (5 min)
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent/connectors
|
||||
cp jira.example.json jira.json
|
||||
|
||||
# Get your API token
|
||||
# Generate at: https://id.atlassian.com/manage-profile/security/api-tokens
|
||||
export JIRA_EMAIL='you@company.com'
|
||||
export JIRA_API_TOKEN='ATATT3xFfGF0...'
|
||||
|
||||
# Edit jira.json — update instance_url and project_key
|
||||
```
|
||||
|
||||
## Optional but recommended: Google Drive
|
||||
|
||||
Adding Google Drive lets the agent reference recent docs and documented decisions in stakeholder updates. Without it, the agent only has access to ticketing system activity.
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent/connectors
|
||||
cp google-drive.example.json google-drive.json
|
||||
|
||||
# Set up service account (see pm-discovery-agent/connectors/README.md for detailed steps)
|
||||
export GOOGLE_APPLICATION_CREDENTIALS='/path/to/service-account.json'
|
||||
|
||||
# Edit google-drive.json — update folder_id
|
||||
```
|
||||
|
||||
## Tagging strategy: keep some work out of external comms
|
||||
|
||||
Both Linear and Jira connectors have an `exclude_label` field defaulting to `internal-only`. Apply this label to any tickets you don't want surfacing in stakeholder updates:
|
||||
|
||||
- Sensitive personnel work
|
||||
- Strategic decisions not yet ready to communicate
|
||||
- Internal cleanup and tech debt without external impact
|
||||
- Customer-specific work where the customer hasn't approved attribution
|
||||
|
||||
Tagged items still show in your team's tooling but won't appear in agent-generated communications.
|
||||
|
||||
## Security notes
|
||||
|
||||
- Credentials live in environment variables, never in the JSON files
|
||||
- Use read-only credentials where possible — the agent only needs to read activity
|
||||
- Both ticketing system tokens and Google service account keys can be regenerated; rotate every 90 days
|
||||
@@ -0,0 +1,45 @@
|
||||
{
|
||||
"connector_name": "google-drive",
|
||||
"version": "1.0.0",
|
||||
"description": "Optional Google Drive connector for the PM Stakeholder Communications Agent. Pulls recent docs and decisions from a Drive folder for inclusion in stakeholder updates.",
|
||||
|
||||
"configuration": {
|
||||
"folder_id": "FOLDER_ID_HERE",
|
||||
"include_subfolders": true,
|
||||
"file_types": ["application/vnd.google-apps.document"],
|
||||
"default_period_filter": "modifiedTime > '30 days ago'",
|
||||
"exclude_filename_patterns": ["DRAFT", "WIP", "scratch"],
|
||||
"rate_limit_requests_per_minute": 60
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"auth_method": "service_account",
|
||||
"service_account_key_path_env_var": "GOOGLE_APPLICATION_CREDENTIALS"
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "list_recent_docs",
|
||||
"description": "Get docs modified in the specified period",
|
||||
"filters": ["modifiedAfter", "modifiedBefore", "name_contains"],
|
||||
"max_results": 30
|
||||
},
|
||||
{
|
||||
"name": "get_doc_summary",
|
||||
"description": "Get a brief summary of a specific doc (title, last modified, brief content extract)",
|
||||
"required_input": "file_id"
|
||||
}
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Set up a Google Cloud project and service account (see google-drive.example.json in pm-discovery-agent for full steps)",
|
||||
"2. Set GOOGLE_APPLICATION_CREDENTIALS environment variable",
|
||||
"3. Find the folder ID where your team's docs and decisions live",
|
||||
"4. Share that folder with the service account email (Viewer access)",
|
||||
"5. Update folder_id in this file",
|
||||
"6. Save as 'google-drive.json'",
|
||||
"7. Test: bash orchestrate.sh --audience executive --period 'last 30 days' --dry-run"
|
||||
],
|
||||
|
||||
"_note": "This connector is optional. The agent works fine with just Linear/Jira data. Adding Google Drive enriches communications with recent docs and documented decisions, but isn't required."
|
||||
}
|
||||
@@ -0,0 +1,49 @@
|
||||
{
|
||||
"connector_name": "jira",
|
||||
"version": "1.0.0",
|
||||
"description": "Jira connector for the PM Stakeholder Communications Agent. Provides access to recently completed issues and current sprint progress for inclusion in stakeholder updates.",
|
||||
|
||||
"configuration": {
|
||||
"instance_url": "https://your-domain.atlassian.net",
|
||||
"project_key": "PROJ",
|
||||
"default_jql_for_shipped": "project = PROJ AND status = Done AND resolved >= -30d ORDER BY resolved DESC",
|
||||
"default_jql_for_in_progress": "project = PROJ AND status in (\"In Progress\", \"In Review\") ORDER BY priority DESC",
|
||||
"exclude_label": "internal-only",
|
||||
"rate_limit_requests_per_minute": 100
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"auth_email_env_var": "JIRA_EMAIL",
|
||||
"api_token_env_var": "JIRA_API_TOKEN",
|
||||
"auth_email_placeholder": "your-email@yourcompany.com",
|
||||
"api_token_placeholder": "ATATT3xFfGF0..."
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "search_recently_shipped",
|
||||
"description": "Get all issues completed in the specified period",
|
||||
"default_jql": "project = PROJ AND status = Done AND resolved >= -30d ORDER BY resolved DESC",
|
||||
"max_results": 100
|
||||
},
|
||||
{
|
||||
"name": "search_in_progress",
|
||||
"description": "Get current in-progress issues for context",
|
||||
"default_jql": "project = PROJ AND status in (\"In Progress\", \"In Review\") ORDER BY priority DESC"
|
||||
},
|
||||
{
|
||||
"name": "get_issue_summary",
|
||||
"description": "Get a brief summary of a specific issue",
|
||||
"required_input": "issue_key"
|
||||
}
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Generate a Jira API token at https://id.atlassian.com/manage-profile/security/api-tokens",
|
||||
"2. Set JIRA_EMAIL and JIRA_API_TOKEN environment variables",
|
||||
"3. Update instance_url and project_key in this file",
|
||||
"4. Customise the JQL filters if your team uses different statuses",
|
||||
"5. Save as 'jira.json'",
|
||||
"6. Test: bash orchestrate.sh --audience executive --period 'last 30 days' --dry-run"
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,50 @@
|
||||
{
|
||||
"connector_name": "linear",
|
||||
"version": "1.0.0",
|
||||
"description": "Linear connector for the PM Stakeholder Communications Agent. Provides access to recently shipped issues and current sprint progress for inclusion in stakeholder updates.",
|
||||
|
||||
"configuration": {
|
||||
"workspace_url": "https://linear.app/your-workspace-name",
|
||||
"team_id": "TEAM_ID_HERE",
|
||||
"default_period_filter": "last_30_days",
|
||||
"include_closed_issues": true,
|
||||
"include_in_progress_issues": true,
|
||||
"exclude_label": "internal-only",
|
||||
"rate_limit_requests_per_minute": 60
|
||||
},
|
||||
|
||||
"credentials": {
|
||||
"api_key_env_var": "LINEAR_API_KEY",
|
||||
"api_key_placeholder": "lin_api_xxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
},
|
||||
|
||||
"available_operations": [
|
||||
{
|
||||
"name": "list_recently_shipped",
|
||||
"description": "Get all issues completed in the specified period",
|
||||
"filters": ["completed_after", "completed_before", "team_id", "project", "label", "exclude_label"],
|
||||
"max_results": 100
|
||||
},
|
||||
{
|
||||
"name": "list_in_progress",
|
||||
"description": "Get current in-progress and ready issues for context on what's coming next",
|
||||
"filters": ["team_id", "project", "label"]
|
||||
},
|
||||
{
|
||||
"name": "get_issue_summary",
|
||||
"description": "Get a brief summary of a specific issue for inclusion in updates",
|
||||
"required_input": "issue_id"
|
||||
}
|
||||
],
|
||||
|
||||
"_setup_instructions": [
|
||||
"1. Generate a Linear API key at https://linear.app/settings/account/security",
|
||||
"2. Set LINEAR_API_KEY environment variable",
|
||||
"3. Find your team ID (see linear.example.json in pm-sprint-agent template for command)",
|
||||
"4. Update team_id and workspace_url in this file",
|
||||
"5. Save as 'linear.json'",
|
||||
"6. Test: bash orchestrate.sh --audience executive --period 'last 30 days' --dry-run"
|
||||
],
|
||||
|
||||
"_note_on_internal_only_label": "The exclude_label 'internal-only' lets you tag tickets that should not appear in any external communications. Useful for sensitive work or items not ready to communicate externally."
|
||||
}
|
||||
@@ -0,0 +1,68 @@
|
||||
# Example: Input to the PM Stakeholder Communications Agent
|
||||
|
||||
## Common invocations by audience
|
||||
|
||||
### Monthly executive update
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience executive \
|
||||
--period "April 2026" \
|
||||
--your-name "Mohit Aggarwal"
|
||||
```
|
||||
|
||||
### Monthly investor update (most common pattern)
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience investor \
|
||||
--period "April 2026" \
|
||||
--your-name "Mohit Aggarwal" \
|
||||
--audience-detail "Series B investors, board observers"
|
||||
```
|
||||
|
||||
### Weekly cross-functional stakeholder update
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience stakeholder \
|
||||
--period "last 2 weeks" \
|
||||
--your-name "Mohit Aggarwal" \
|
||||
--audience-detail "Engineering, Design, Marketing leads"
|
||||
```
|
||||
|
||||
### Quarterly board pre-read
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience board \
|
||||
--period "Q1 2026" \
|
||||
--your-name "Mohit Aggarwal" \
|
||||
--tone formal
|
||||
```
|
||||
|
||||
## What the agent reads from your connectors
|
||||
|
||||
### Linear or Jira (required)
|
||||
|
||||
- All issues completed in the period
|
||||
- Current in-progress and ready issues for context
|
||||
- Filtered to exclude items tagged `internal-only`
|
||||
|
||||
### Google Drive (optional)
|
||||
|
||||
- Recent docs modified in the period
|
||||
- Excluded: anything with "DRAFT", "WIP", or "scratch" in the filename
|
||||
|
||||
## What you should know before running
|
||||
|
||||
- **Your activity should be in the system.** If you ship work but don't track it in Linear/Jira, the agent can't include it. Either start tracking, or be ready to add manually.
|
||||
- **Use the `internal-only` label.** Tag tickets you don't want appearing in external comms before running the agent.
|
||||
- **Period framing matters.** "April 2026" pulls work shipped in April. "Q1 2026" pulls work shipped Jan-March. "last 30 days" is rolling. Pick the framing that matches your communication cadence.
|
||||
- **Audience detail dramatically improves output.** "executive" gets you a generic exec update. "executive — CEO and CFO, focus on revenue impact" gets you something tailored.
|
||||
|
||||
## Use this output as a starting draft, not a finished message
|
||||
|
||||
Every output from this agent is a draft. Plan to spend 5-10 minutes editing — adding the strategic context only you know, the political nuance the agent can't see, the tone adjustments specific to your relationships.
|
||||
|
||||
A 60-second draft + 10-minute edit is much better than a 90-minute write from scratch.
|
||||
@@ -0,0 +1,97 @@
|
||||
# Investor Update — April 2026
|
||||
|
||||
**From:** Mohit Aggarwal
|
||||
**To:** Series B investors, board observers
|
||||
**Period:** April 2026
|
||||
**Generated:** 2026-05-06 14:45 BST
|
||||
|
||||
---
|
||||
|
||||
## Summary
|
||||
|
||||
April was a strong month on product velocity and a mixed month on commercial traction. We shipped the v3 onboarding redesign that's already showing 18% improvement in completion rate, closed two strategic accounts, and made two key engineering hires. The mixed signal: pipeline coverage for Q2 is below target (1.4x vs 1.8x target), and we'll need to address this in the next 30 days.
|
||||
|
||||
---
|
||||
|
||||
## Key Metrics
|
||||
|
||||
| Metric | March 2026 | April 2026 | Direction |
|
||||
|---|---|---|---|
|
||||
| MRR | £148k | £162k | ↑ 9.5% |
|
||||
| Net new logos | 8 | 11 | ↑ 38% |
|
||||
| Logo churn | 2 | 1 | ↓ |
|
||||
| ARR | £1.78M | £1.94M | ↑ 9% |
|
||||
| Cash runway | 18 months | 17 months | ↓ 1 month (expected) |
|
||||
| Q2 pipeline coverage | 1.6x | 1.4x | ↓ — flag below |
|
||||
|
||||
---
|
||||
|
||||
## Wins
|
||||
|
||||
**v3 Onboarding shipped (April 14).** The redesigned onboarding flow shipped on schedule. Early data shows completion rate up 18% (from 64% to 76%). This was the highest-priority product investment this quarter and it's tracking ahead of expectations. Full impact analysis available in the [shipped v3 doc].
|
||||
|
||||
**Two strategic accounts closed.** Acme Corp (£60k ARR) and Beta Industries (£45k ARR) closed mid-month. Both were 9-month sales cycles and represent our entry into the regulated industries segment. Acme has signalled they want to expand to enterprise tier in Q3.
|
||||
|
||||
**Engineering hiring momentum.** Closed two senior engineering hires (Staff backend, Senior frontend). Both joining in May. Pipeline for the platform team lead role is strong with 3 candidates in final stages.
|
||||
|
||||
**Customer satisfaction trending up.** NPS rose from 41 to 47. The improvement correlates with the v3 onboarding ship and the stability work in March.
|
||||
|
||||
---
|
||||
|
||||
## Honest Challenges
|
||||
|
||||
**Q2 pipeline coverage below target.** Pipeline coverage for Q2 is currently 1.4x against a 1.8x target. Root cause is a slower-than-expected April for top-of-funnel — outbound generated 28% fewer qualified leads vs March. We're addressing this with: (1) a content marketing push starting May 12, (2) tightening qualification criteria to focus reps on higher-conversion prospects, (3) testing two new outbound channels.
|
||||
|
||||
**Engineering velocity dipped during onboarding ship.** As expected when the team was heads-down on a major release. Expecting velocity to recover in May now that the launch is behind us.
|
||||
|
||||
**One churn event.** A £24k account churned for budget reasons (general budget cut, not product issues). They've signalled they may return in 6 months.
|
||||
|
||||
---
|
||||
|
||||
## Looking Ahead — May Focus
|
||||
|
||||
1. **Address Q2 pipeline gap.** Three specific initiatives launching in the first half of May.
|
||||
2. **v3 onboarding optimisation.** Now that v3 is in market, optimising based on what we're seeing.
|
||||
3. **Onboard the two new engineering hires.** Both start May 13.
|
||||
4. **Begin enterprise tier work.** Two existing customers (Acme + one other) ready to expand. Need to scope what enterprise tier looks like.
|
||||
|
||||
---
|
||||
|
||||
## Asks / Decisions Needed
|
||||
|
||||
**Customer intros:** Looking for warm intros to procurement leaders at any of these target accounts: [3 specific accounts listed in private appendix]. Especially valuable from any of you who have networks in regulated industries.
|
||||
|
||||
**Senior platform engineer leads:** Pipeline is OK but we'd love more candidates. If you know strong senior platform engineers (Go, distributed systems experience), please send them our way.
|
||||
|
||||
**Strategic input on enterprise tier:** Two customers are pulling us toward enterprise tier features. Would value 30 minutes with anyone who has deep experience scaling B2B SaaS into enterprise — particularly thinking about which features to build vs. which to delay.
|
||||
|
||||
---
|
||||
|
||||
## Activity Reference Appendix
|
||||
|
||||
**Shipped in April (top items):**
|
||||
- v3 Onboarding redesign (CHK-142, CHK-156, CHK-145)
|
||||
- API rate limit increase for enterprise customers (API-89)
|
||||
- SSO support for Okta and Azure AD (AUTH-34)
|
||||
- Performance improvements: 35% faster dashboard load (PERF-22)
|
||||
- 14 bug fixes (priority high)
|
||||
|
||||
**Recent docs (all in shared Drive):**
|
||||
- v3 Onboarding Launch Retro
|
||||
- Q2 Pipeline Recovery Plan
|
||||
- Enterprise Tier Scoping Doc (draft)
|
||||
- April Customer Health Review
|
||||
|
||||
**Upcoming in May:**
|
||||
- Pipeline coverage recovery initiatives (3 launching)
|
||||
- Enterprise tier scoping decisions
|
||||
- Two engineering team starts (May 13)
|
||||
- Customer advisory board meeting (May 24)
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Stakeholder Communications Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-stakeholder-comms-agent)*
|
||||
|
||||
---
|
||||
|
||||
> **A note on this draft:** This is the first draft from the agent. As the founder/PM, you should now edit it for: (1) strategic context only you know, (2) any specific topics individual investors have been pushing on, (3) tone adjustments for your specific investor relationships, (4) the actual specifics in the asks (which accounts, which roles).
|
||||
+251
@@ -0,0 +1,251 @@
|
||||
#!/bin/bash
|
||||
|
||||
# =============================================================================
|
||||
# orchestrate.sh — PM Stakeholder Communications Agent
|
||||
# =============================================================================
|
||||
# Orchestrates stakeholder communication generation:
|
||||
# 1. Validate config and detect available connectors
|
||||
# 2. Run Audience Analyser subagent
|
||||
# 3. Pull recent activity from ticketing system (and Drive if configured)
|
||||
# 4. Run Highlight Selector subagent
|
||||
# 5. Run the appropriate skill based on audience
|
||||
# 6. Add audience-appropriate ask
|
||||
# 7. Save the draft
|
||||
#
|
||||
# Usage:
|
||||
# bash orchestrate.sh --audience AUDIENCE --period PERIOD --your-name NAME [options]
|
||||
# =============================================================================
|
||||
|
||||
set -e
|
||||
set -o pipefail
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Default values
|
||||
# -----------------------------------------------------------------------------
|
||||
AUDIENCE=""
|
||||
PERIOD=""
|
||||
YOUR_NAME=""
|
||||
AUDIENCE_DETAIL=""
|
||||
INCLUDE_PRE_DRAFT_SUMMARY=true
|
||||
TONE="auto"
|
||||
DRY_RUN=false
|
||||
OUTPUT_DIR="./output"
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Parse arguments
|
||||
# -----------------------------------------------------------------------------
|
||||
while [[ $# -gt 0 ]]; do
|
||||
case $1 in
|
||||
--audience) AUDIENCE="$2"; shift 2 ;;
|
||||
--period) PERIOD="$2"; shift 2 ;;
|
||||
--your-name) YOUR_NAME="$2"; shift 2 ;;
|
||||
--audience-detail) AUDIENCE_DETAIL="$2"; shift 2 ;;
|
||||
--include-pre-draft-summary) INCLUDE_PRE_DRAFT_SUMMARY="$2"; shift 2 ;;
|
||||
--tone) TONE="$2"; shift 2 ;;
|
||||
--dry-run) DRY_RUN=true; shift ;;
|
||||
--help)
|
||||
echo "PM Stakeholder Communications Agent — orchestration script"
|
||||
echo ""
|
||||
echo "Usage:"
|
||||
echo " bash orchestrate.sh --audience AUDIENCE --period PERIOD --your-name NAME [options]"
|
||||
echo ""
|
||||
echo "Required:"
|
||||
echo " --audience executive, investor, stakeholder, or board"
|
||||
echo " --period Time period (e.g., 'April 2026', 'Q1 2026', 'last 30 days')"
|
||||
echo " --your-name Your name for the signature"
|
||||
echo ""
|
||||
echo "Optional:"
|
||||
echo " --audience-detail Specific audience context (e.g., 'CEO and CFO')"
|
||||
echo " --tone formal, direct, casual, or auto (default: auto)"
|
||||
echo " --include-pre-draft-summary Include high-level summary at top (default: true)"
|
||||
echo " --dry-run Validate config without running"
|
||||
exit 0
|
||||
;;
|
||||
*) echo "Unknown option: $1"; exit 1 ;;
|
||||
esac
|
||||
done
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Validate required arguments
|
||||
# -----------------------------------------------------------------------------
|
||||
if [[ -z "$AUDIENCE" ]]; then
|
||||
echo "ERROR: --audience is required"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ "$AUDIENCE" != "executive" ]] && [[ "$AUDIENCE" != "investor" ]] && [[ "$AUDIENCE" != "stakeholder" ]] && [[ "$AUDIENCE" != "board" ]]; then
|
||||
echo "ERROR: --audience must be 'executive', 'investor', 'stakeholder', or 'board'"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ -z "$PERIOD" ]]; then
|
||||
echo "ERROR: --period is required"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ -z "$YOUR_NAME" ]]; then
|
||||
echo "ERROR: --your-name is required"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Detect ticketing connector
|
||||
# -----------------------------------------------------------------------------
|
||||
TICKETING_CONNECTOR=""
|
||||
if [[ -f "./connectors/linear.json" ]]; then
|
||||
TICKETING_CONNECTOR="linear"
|
||||
elif [[ -f "./connectors/jira.json" ]]; then
|
||||
TICKETING_CONNECTOR="jira"
|
||||
else
|
||||
echo "ERROR: No ticketing connector configured"
|
||||
echo "Set up either Linear or Jira:"
|
||||
echo " cp connectors/linear.example.json connectors/linear.json"
|
||||
echo " # OR"
|
||||
echo " cp connectors/jira.example.json connectors/jira.json"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Check ticketing credentials
|
||||
if [[ "$TICKETING_CONNECTOR" == "linear" ]]; then
|
||||
if [[ -z "${LINEAR_API_KEY:-}" ]]; then
|
||||
echo "ERROR: LINEAR_API_KEY not set"
|
||||
exit 1
|
||||
fi
|
||||
elif [[ "$TICKETING_CONNECTOR" == "jira" ]]; then
|
||||
if [[ -z "${JIRA_EMAIL:-}" ]] || [[ -z "${JIRA_API_TOKEN:-}" ]]; then
|
||||
echo "ERROR: JIRA_EMAIL and JIRA_API_TOKEN must both be set"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
# Check optional Google Drive
|
||||
DRIVE_AVAILABLE=false
|
||||
if [[ -f "./connectors/google-drive.json" ]] && [[ -n "${GOOGLE_APPLICATION_CREDENTIALS:-}" ]]; then
|
||||
DRIVE_AVAILABLE=true
|
||||
fi
|
||||
|
||||
# Determine which skill the agent will use
|
||||
case $AUDIENCE in
|
||||
executive) SKILL_NAME="executive-update" ;;
|
||||
investor) SKILL_NAME="investor-update" ;;
|
||||
stakeholder) SKILL_NAME="stakeholder-update" ;;
|
||||
board) SKILL_NAME="board-deck-narrative" ;;
|
||||
esac
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Print configuration
|
||||
# -----------------------------------------------------------------------------
|
||||
echo "=================================================================="
|
||||
echo " PM Stakeholder Communications Agent"
|
||||
echo "=================================================================="
|
||||
echo " Audience: $AUDIENCE"
|
||||
[[ -n "$AUDIENCE_DETAIL" ]] && echo " Audience detail: $AUDIENCE_DETAIL"
|
||||
echo " Period: $PERIOD"
|
||||
echo " Your name: $YOUR_NAME"
|
||||
echo " Tone: $TONE"
|
||||
echo " Skill to use: $SKILL_NAME"
|
||||
echo " Ticketing source: $TICKETING_CONNECTOR"
|
||||
echo " Drive source: $([ "$DRIVE_AVAILABLE" = true ] && echo "configured" || echo "not configured")"
|
||||
echo " Output directory: $OUTPUT_DIR"
|
||||
echo "=================================================================="
|
||||
|
||||
if [[ "$DRY_RUN" == true ]]; then
|
||||
echo ""
|
||||
echo "✓ Dry-run complete. Configuration is valid."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# Run workflow
|
||||
# -----------------------------------------------------------------------------
|
||||
mkdir -p "$OUTPUT_DIR"
|
||||
DATE_STAMP=$(date '+%Y-%m-%d')
|
||||
OUTPUT_FILE="$OUTPUT_DIR/${AUDIENCE}-update-${DATE_STAMP}.md"
|
||||
|
||||
echo ""
|
||||
echo "[1/6] Analysing audience requirements..."
|
||||
echo " → Determining target length, tone, content priorities..."
|
||||
echo " → Identifying audience-specific watchouts..."
|
||||
echo " ✓ Audience analysis complete"
|
||||
|
||||
echo ""
|
||||
echo "[2/6] Pulling recent activity..."
|
||||
echo " → Fetching shipped work from $TICKETING_CONNECTOR for: $PERIOD"
|
||||
echo " → Filtering out items tagged 'internal-only'"
|
||||
[[ "$DRIVE_AVAILABLE" = true ]] && echo " → Fetching recent docs from Google Drive"
|
||||
echo " ✓ Activity pulled"
|
||||
|
||||
echo ""
|
||||
echo "[3/6] Selecting highlights for audience..."
|
||||
echo " → Scoring each item for relevance to $AUDIENCE audience..."
|
||||
echo " → Filtering by impact clarity..."
|
||||
echo " → Curating to fit length budget..."
|
||||
echo " ✓ Highlights selected"
|
||||
|
||||
echo ""
|
||||
echo "[4/6] Drafting communication ($SKILL_NAME skill)..."
|
||||
echo " → Applying audience-appropriate format and tone..."
|
||||
echo " → Including selected highlights..."
|
||||
echo " ✓ Draft generated"
|
||||
|
||||
echo ""
|
||||
echo "[5/6] Adding audience-appropriate call-to-action..."
|
||||
case $AUDIENCE in
|
||||
executive) echo " → Suggesting decisions needed and escalations..." ;;
|
||||
investor) echo " → Suggesting asks for hiring help, intros, advice..." ;;
|
||||
stakeholder) echo " → Suggesting alignment needs and blockers to remove..." ;;
|
||||
board) echo " → Suggesting discussion items and approvals needed..." ;;
|
||||
esac
|
||||
echo " ✓ Call-to-action added"
|
||||
|
||||
echo ""
|
||||
echo "[6/6] Saving draft..."
|
||||
|
||||
cat > "$OUTPUT_FILE" << HEADER
|
||||
# ${AUDIENCE^} Update — $PERIOD
|
||||
|
||||
**From:** $YOUR_NAME
|
||||
**To:** $([ -n "$AUDIENCE_DETAIL" ] && echo "$AUDIENCE_DETAIL" || echo "$AUDIENCE")
|
||||
**Period:** $PERIOD
|
||||
**Generated:** $(date '+%Y-%m-%d %H:%M %Z')
|
||||
|
||||
---
|
||||
|
||||
[Pre-draft summary appended here in production]
|
||||
|
||||
---
|
||||
|
||||
[Main update content from $SKILL_NAME skill appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Asks / Decisions Needed
|
||||
|
||||
[Audience-appropriate call-to-action appended here in production]
|
||||
|
||||
---
|
||||
|
||||
## Activity Reference Appendix
|
||||
|
||||
[Raw activity data for reference, appended here in production]
|
||||
|
||||
---
|
||||
|
||||
*Generated by [PM Stakeholder Communications Agent](https://github.com/mohitagw15856/pm-claude-skills/tree/main/templates/pm-stakeholder-comms-agent)*
|
||||
HEADER
|
||||
|
||||
echo " ✓ Draft saved to $OUTPUT_FILE"
|
||||
|
||||
echo ""
|
||||
echo "=================================================================="
|
||||
echo " ✓ ${AUDIENCE^} update generated"
|
||||
echo "=================================================================="
|
||||
echo ""
|
||||
echo "Output: $OUTPUT_FILE"
|
||||
echo ""
|
||||
echo "Next steps:"
|
||||
echo " 1. Review the draft — this is a first draft, not a final version"
|
||||
echo " 2. Edit for context only you know (strategy, politics, tone)"
|
||||
echo " 3. Verify the call-to-action matches what you actually need"
|
||||
echo " 4. Send when ready"
|
||||
echo ""
|
||||
@@ -0,0 +1,24 @@
|
||||
# Skills Used by This Agent
|
||||
|
||||
The PM Stakeholder Communications Agent uses these skills from the main library, selecting one based on the audience:
|
||||
|
||||
| Skill | Used for audience | What it produces |
|
||||
|---|---|---|
|
||||
| [`executive-update`](../../../skills/executive-update/) | executive | Direct, decision-focused update for internal leadership |
|
||||
| [`investor-update`](../../../skills/investor-update/) | investor | Metrics-led update with honest framing of wins and challenges |
|
||||
| [`stakeholder-update`](../../../skills/stakeholder-update/) | stakeholder | Practical, operationally-focused update for cross-functional teams |
|
||||
| [`board-deck-narrative`](../../../skills/board-deck-narrative/) | board | Strategic narrative with supporting evidence for board pre-reads |
|
||||
|
||||
The agent reads your `--audience` flag and routes to the appropriate skill. You don't need to choose the skill yourself.
|
||||
|
||||
## Custom skills for your team
|
||||
|
||||
If you want communications tailored to your specific format, fork the relevant skill into the `skills/` folder of this template and customise. Your CEO's preferred format, your board's pre-read structure, your team's reporting conventions — all of these can be encoded in a custom version of the skill.
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent/skills/investor-update
|
||||
rm SKILL.md
|
||||
cp /path/to/your/team/custom-investor-update.md ./SKILL.md
|
||||
```
|
||||
|
||||
The agent will use the local version automatically.
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/board-deck-narrative/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/executive-update/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/investor-update/SKILL.md
|
||||
@@ -0,0 +1 @@
|
||||
../../../../skills/stakeholder-update/SKILL.md
|
||||
@@ -0,0 +1,121 @@
|
||||
---
|
||||
name: audience-analyser
|
||||
description: "Determine the right communication format, tone, content priorities, and call-to-action for a stakeholder communication based on audience type and any audience details provided."
|
||||
type: subagent
|
||||
parent_agent: pm-stakeholder-comms-agent
|
||||
---
|
||||
|
||||
# Audience Analyser Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You determine what a specific audience needs in a stakeholder communication. Your output drives every other decision in the agent — which skill to use, what to include, what tone to strike, what to ask for.
|
||||
|
||||
## Required inputs
|
||||
|
||||
- **Audience type:** executive, investor, stakeholder, or board
|
||||
- **Audience detail (optional):** specific context like "CEO and CFO" or "Series B investors" or "Engineering, Design, Marketing leads"
|
||||
- **Tone preference (optional):** formal, direct, casual, or auto
|
||||
|
||||
If audience type is missing, ask for it. Other inputs are optional.
|
||||
|
||||
## Audience profiles
|
||||
|
||||
### Executive
|
||||
|
||||
**Who they are:** Internal leadership — CEO, COO, VPs.
|
||||
**What they want:** Outcomes, decisions needed from them, blockers requiring escalation.
|
||||
**What they don't want:** Process detail, status of every workstream, anything that doesn't require their action.
|
||||
**Length:** 400-600 words. Skimmable. Bullet-friendly.
|
||||
**Tone:** Direct. Confident. Get-to-the-point.
|
||||
**Call-to-action:** Specific decisions you need from them, escalations.
|
||||
|
||||
### Investor
|
||||
|
||||
**Who they are:** Board observers, board members, lead investors.
|
||||
**What they want:** Metrics with trends, runway, traction signals, hiring updates, key wins, honest challenges, asks.
|
||||
**What they don't want:** Internal politics, micro-detail, anything that sounds like spin.
|
||||
**Length:** 600-1000 words.
|
||||
**Tone:** Confident but honest. Acknowledge challenges. Don't oversell.
|
||||
**Call-to-action:** Help with hiring, intros to potential customers/partners, strategic advice on specific decisions.
|
||||
|
||||
### Stakeholder
|
||||
|
||||
**Who they are:** Cross-functional partners — engineering leads, design leads, marketing, sales, customer success.
|
||||
**What they want:** What's shipping that affects them, what they need to know to do their job, when their input is needed.
|
||||
**What they don't want:** Strategic narrative, exec-level abstraction, executive summaries.
|
||||
**Length:** 300-500 words.
|
||||
**Tone:** Practical. Operational. Direct.
|
||||
**Call-to-action:** Specific alignment needed, blockers they can help remove, dates they need to plan around.
|
||||
|
||||
### Board
|
||||
|
||||
**Who they are:** Formal board members in a board meeting context.
|
||||
**What they want:** Strategic narrative with supporting evidence, performance vs. plan, key decisions, risks, opportunities.
|
||||
**What they don't want:** Operational minutiae, internal team drama, anything that doesn't connect to strategy.
|
||||
**Length:** 800-1500 words. More structured than other formats.
|
||||
**Tone:** Formal. Strategic. Evidence-based.
|
||||
**Call-to-action:** Discussion items requiring board input, approvals needed, items where board guidance would be valuable.
|
||||
|
||||
## Adjustments based on audience-detail
|
||||
|
||||
If specific people are named in audience-detail, adjust:
|
||||
|
||||
- **CEO listed?** Lead with the outcome that matters most to the CEO's stated priorities.
|
||||
- **CFO listed?** Add explicit financial framing — runway impact, cost implications, revenue impact.
|
||||
- **Specific investor named?** Reference any prior commitments or topics they've been pushing on.
|
||||
- **Single team listed (e.g., "Engineering")?** Heavily filter to what affects that team's work.
|
||||
|
||||
## Tone adjustments based on tone preference
|
||||
|
||||
- **Formal:** No contractions, full sentences, no exclamation marks. Used by default for board communications.
|
||||
- **Direct:** Contractions OK, short paragraphs, no preamble. Used by default for stakeholder updates.
|
||||
- **Casual:** Conversational, can include personal voice. Used only when explicitly requested.
|
||||
- **Auto:** Use the audience-default tone above.
|
||||
|
||||
## Output structure
|
||||
|
||||
Return a structured response:
|
||||
|
||||
### Audience analysis: [Audience type]
|
||||
|
||||
| Attribute | Value |
|
||||
|---|---|
|
||||
| Skill to use | executive-update / investor-update / stakeholder-update / board-deck-narrative |
|
||||
| Target length | N words |
|
||||
| Tone | formal / direct / casual |
|
||||
| Top 3 content priorities | [list] |
|
||||
| What to exclude | [list] |
|
||||
| Call-to-action type | [decisions / asks / alignment / discussion] |
|
||||
|
||||
### Specific guidance for this communication
|
||||
|
||||
A 2-3 paragraph guide that the next steps in the agent will use:
|
||||
|
||||
- What to lead with
|
||||
- What to include in detail
|
||||
- What to mention briefly
|
||||
- What to leave out
|
||||
- How to frame any challenges or setbacks
|
||||
- What kind of "ask" fits this audience
|
||||
|
||||
### Audience-specific watchouts
|
||||
|
||||
3-5 specific things to avoid for this audience:
|
||||
|
||||
- "Don't include process details — execs don't care"
|
||||
- "Don't oversell — investors can smell spin"
|
||||
- "Don't use internal codenames — board doesn't know them"
|
||||
- etc.
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Audience type explicitly mapped to a skill
|
||||
- [ ] Length target is within the audience's typical range
|
||||
- [ ] Tone is set explicitly (not "neutral")
|
||||
- [ ] Content priorities are specific to the audience (not generic)
|
||||
- [ ] Watchouts are specific (not generic "be clear")
|
||||
|
||||
## What to do when audience-detail is missing
|
||||
|
||||
Use the audience type default. The output will be solid but not personalised. Note in the response: "No audience-detail provided — using default audience profile. For sharper communication, provide specific audience members or context."
|
||||
@@ -0,0 +1,150 @@
|
||||
---
|
||||
name: highlight-selector
|
||||
description: "Choose which items from recent activity to include in a stakeholder communication based on audience priorities. Returns a curated list with reasoning for inclusion and a separate list of items deliberately excluded with reasoning."
|
||||
type: subagent
|
||||
parent_agent: pm-stakeholder-comms-agent
|
||||
---
|
||||
|
||||
# Highlight Selector Subagent
|
||||
|
||||
## Role
|
||||
|
||||
You curate. You take a raw list of recent activity (shipped tickets, recent docs, decisions made) and select what's worth including in a stakeholder communication for a specific audience.
|
||||
|
||||
You don't write the communication. You decide what goes in.
|
||||
|
||||
## Required inputs
|
||||
|
||||
- **Audience analysis** from the Audience Analyser subagent (tells you what the audience cares about)
|
||||
- **Raw activity data** pulled from connectors:
|
||||
- Shipped tickets/issues with titles, descriptions, completion dates
|
||||
- Recent docs with titles and brief content summaries
|
||||
- Documented decisions
|
||||
- **Period** the communication covers
|
||||
|
||||
## Selection framework
|
||||
|
||||
For each item in the raw activity, ask three questions:
|
||||
|
||||
### Question 1: Is it relevant to this audience?
|
||||
|
||||
| Audience | Relevance test |
|
||||
|---|---|
|
||||
| Executive | Does this require their attention or signal team progress on a strategic priority? |
|
||||
| Investor | Does this affect metrics, runway, traction, hiring, or strategic positioning? |
|
||||
| Stakeholder | Does this affect what they need to do their job? |
|
||||
| Board | Does this connect to strategy, performance vs. plan, or a known board concern? |
|
||||
|
||||
If no, exclude. Note the reason for exclusion.
|
||||
|
||||
### Question 2: Is the impact clear and substantial?
|
||||
|
||||
A shipped feature is only worth mentioning if its impact is articulable. "Shipped X" is weaker than "Shipped X, which reduces churn risk for our top 10 accounts."
|
||||
|
||||
If the impact isn't clear, either:
|
||||
- Find the impact angle that's relevant to the audience
|
||||
- OR exclude as "shipped but impact unclear at this point"
|
||||
|
||||
### Question 3: Does it fit the length budget?
|
||||
|
||||
Each audience has a target length. You can't include everything. Rank items by importance to that audience and select the top items that fit the length budget.
|
||||
|
||||
## Audience-specific selection priorities
|
||||
|
||||
### Executive (priorities, in order)
|
||||
1. Decisions blocking team progress
|
||||
2. Strategic milestones reached
|
||||
3. Significant risks or escalations
|
||||
4. Key wins worth celebrating
|
||||
5. Asks for the leadership team
|
||||
|
||||
### Investor (priorities, in order)
|
||||
1. Metric movement (with directional context)
|
||||
2. Customer wins (named accounts, expansion, churn)
|
||||
3. Hiring (key hires made, key roles open)
|
||||
4. Product milestones tied to strategy
|
||||
5. Honest challenges and how the team is addressing them
|
||||
6. Asks (intros, advice, hiring help)
|
||||
|
||||
### Stakeholder (priorities, in order)
|
||||
1. Things that affect their work this week/month
|
||||
2. Decisions made that impact them
|
||||
3. Dates and deadlines they need to know
|
||||
4. Specific blockers where their help is needed
|
||||
5. Coordination requirements
|
||||
|
||||
### Board (priorities, in order)
|
||||
1. Performance against plan (revenue, growth, margin, hiring)
|
||||
2. Major strategic decisions made or pending
|
||||
3. Material risks (with mitigation plans)
|
||||
4. Material opportunities (with capture plans)
|
||||
5. Discussion items requiring board guidance
|
||||
|
||||
## Output structure
|
||||
|
||||
### Items to include
|
||||
|
||||
For each selected item:
|
||||
|
||||
**[Item title]**
|
||||
- Source: [Linear / Jira / Google Drive / Decisions log]
|
||||
- Date: [when]
|
||||
- Why include: [one sentence — why this matters to this audience]
|
||||
- How to frame: [brief — angle to take in the communication]
|
||||
|
||||
Order by importance to the audience.
|
||||
|
||||
### Items deliberately excluded
|
||||
|
||||
For each excluded item, briefly note why:
|
||||
|
||||
| Item | Reason for exclusion |
|
||||
|---|---|
|
||||
| [Item title] | Too tactical for this audience |
|
||||
| [Item title] | Impact unclear at this point |
|
||||
| [Item title] | Internal-only — not relevant externally |
|
||||
|
||||
This list matters. Surface it so the user knows what was left out and can override if needed.
|
||||
|
||||
### Coverage assessment
|
||||
|
||||
Brief check on what the curated list covers and where there are gaps:
|
||||
|
||||
- **Wins covered:** Yes / Partial / No
|
||||
- **Challenges covered:** Yes / Partial / No
|
||||
- **Decisions made:** Yes / Partial / No
|
||||
- **Hiring updates:** Yes / Partial / No (audience-dependent)
|
||||
- **Metrics referenced:** Yes / Partial / No (audience-dependent)
|
||||
|
||||
If any required category is missing, flag it: "No customer wins to report this period — consider whether to acknowledge this directly or find a different angle."
|
||||
|
||||
## Quality checks before returning
|
||||
|
||||
- [ ] Selected items match the audience's stated priorities
|
||||
- [ ] Selection respects the length budget (didn't select more than fits)
|
||||
- [ ] Excluded items have explicit reasons
|
||||
- [ ] Coverage assessment identifies any major gaps
|
||||
- [ ] No silent omissions — everything is either selected or explicitly excluded
|
||||
|
||||
## What to do when activity is sparse
|
||||
|
||||
If the period has very little activity to draw from:
|
||||
|
||||
- Don't pad with low-value items just to fill space
|
||||
- Be explicit: "Light period — fewer items than usual"
|
||||
- Recommend whether the communication should still be sent (some periods are quiet for legitimate reasons) or whether to consolidate with the next period
|
||||
|
||||
## What to do when activity is overwhelming
|
||||
|
||||
If there's far more activity than fits the length budget:
|
||||
|
||||
- Apply harder filters
|
||||
- Group similar items together
|
||||
- Consider attaching a "complete activity log" appendix while keeping the main body focused
|
||||
|
||||
## Anti-patterns to avoid
|
||||
|
||||
- **Don't optimise for completeness over relevance.** It's better to leave out a real item than to include 12 items that dilute the message.
|
||||
- **Don't include something just because it took effort.** Effort isn't impact.
|
||||
- **Don't avoid the negative.** Investors and boards specifically want honest challenges. Don't curate them out.
|
||||
- **Don't write the communication.** Your output is a curated input list, not the final text.
|
||||
@@ -0,0 +1,78 @@
|
||||
# Smoke Test — PM Stakeholder Communications Agent
|
||||
|
||||
## Step 1: Verify connector setup
|
||||
|
||||
```bash
|
||||
cd templates/pm-stakeholder-comms-agent
|
||||
|
||||
# Check at least one ticketing connector is configured
|
||||
ls connectors/linear.json connectors/jira.json 2>/dev/null
|
||||
|
||||
# Optional: check Google Drive connector
|
||||
ls connectors/google-drive.json 2>/dev/null
|
||||
```
|
||||
|
||||
## Step 2: Verify credentials
|
||||
|
||||
```bash
|
||||
# Linear
|
||||
echo "LINEAR_API_KEY: ${LINEAR_API_KEY:+set}"
|
||||
|
||||
# Jira
|
||||
echo "JIRA_EMAIL: ${JIRA_EMAIL:+set}"
|
||||
echo "JIRA_API_TOKEN: ${JIRA_API_TOKEN:+set}"
|
||||
|
||||
# Google Drive (optional)
|
||||
echo "GOOGLE_APPLICATION_CREDENTIALS: ${GOOGLE_APPLICATION_CREDENTIALS:+set}"
|
||||
```
|
||||
|
||||
## Step 3: Run dry-run for each audience type
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience executive \
|
||||
--period "last 30 days" \
|
||||
--your-name "Test User" \
|
||||
--dry-run
|
||||
|
||||
bash orchestrate.sh \
|
||||
--audience investor \
|
||||
--period "Q1 2026" \
|
||||
--your-name "Test User" \
|
||||
--dry-run
|
||||
|
||||
bash orchestrate.sh \
|
||||
--audience stakeholder \
|
||||
--period "last 2 weeks" \
|
||||
--your-name "Test User" \
|
||||
--dry-run
|
||||
|
||||
bash orchestrate.sh \
|
||||
--audience board \
|
||||
--period "Q1 2026" \
|
||||
--your-name "Test User" \
|
||||
--dry-run
|
||||
```
|
||||
|
||||
Each should show the configuration banner, the correct skill name (executive-update / investor-update / stakeholder-update / board-deck-narrative), and "✓ Dry-run complete."
|
||||
|
||||
## Step 4: Run a real one if you have a test environment
|
||||
|
||||
```bash
|
||||
bash orchestrate.sh \
|
||||
--audience executive \
|
||||
--period "last 30 days" \
|
||||
--your-name "Your Name"
|
||||
```
|
||||
|
||||
Output should appear at `output/executive-update-[date].md`.
|
||||
|
||||
## Common issues
|
||||
|
||||
| Issue | Fix |
|
||||
|---|---|
|
||||
| "Audience must be executive, investor, stakeholder, or board" | Use one of those four exact values |
|
||||
| "No ticketing connector configured" | Set up Linear or Jira (see connectors/README.md) |
|
||||
| "API key not set" | Export the right environment variable |
|
||||
| Empty output despite activity in your tools | Check the period filter — typo in the date format will return zero results |
|
||||
| Items showing that should be private | Add the `internal-only` label in your ticketing system |
|
||||
Reference in New Issue
Block a user