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.
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mohitagw15856
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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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| 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.
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### 1. Create a Google Cloud project
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- Go to https://console.cloud.google.com/
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- Click "Select a project" > "New Project"
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- Name it "PM Discovery Agent"
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- Click Create
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### 2. Enable the APIs
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- In the project, search for "Google Drive API" in the API library
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- Click Enable
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- Search for "Google Docs API"
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- Click Enable
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### 3. Create a service account
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- Go to IAM & Admin > Service Accounts
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- Click "+ Create Service Account"
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- Name: "pm-discovery-reader"
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- Description: "Read-only access for PM Discovery Agent"
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- Click Create
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- Skip the optional permissions step
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- Click Done
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### 4. Download the service account key
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- Click on the service account you just created
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- Go to the "Keys" tab
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- Click "Add Key" > "Create new key"
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- Choose JSON
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- Save the file somewhere secure (e.g., `~/.config/pm-discovery-agent/service-account.json`)
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### 5. Set the environment variable
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```bash
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export GOOGLE_APPLICATION_CREDENTIALS='/Users/yourname/.config/pm-discovery-agent/service-account.json'
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```
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To make permanent, add to `~/.zshrc` or `~/.bashrc`.
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### 6. Share your interview folder with the service account
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- Find the service account email (it looks like `pm-discovery-reader@your-project.iam.gserviceaccount.com`)
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- Open your interview notes folder in Google Drive
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- Click Share
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- Paste the service account email
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- Set permission to Viewer
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- Click Send
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### 7. Find your folder ID
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Open the folder in Google Drive. The URL looks like: `drive.google.com/drive/folders/FOLDER_ID_HERE`
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Copy the ID after `/folders/`.
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### 8. Configure the connector
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```bash
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cp google-drive.example.json google-drive.json
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```
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Open `google-drive.json` and update:
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- `folder_id` — paste the ID from step 7
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### 9. 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 google-drive --dry-run
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```
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## Building a connector for another system
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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:
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- **Dovetail** — has a research API; build a connector for the analysis endpoint
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- **Granola / Otter / Fathom** — meeting recorders; build a connector that pulls transcripts
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- **Reflect / Roam / Logseq** — personal note-taking apps; build a connector for the markdown files
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- **Coda / Airtable** — alternative databases; build a connector for the rows API
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- **Local files** — markdown files in a folder; build a simple file-reading connector
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A connector needs three things:
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1. A configuration file defining the data source URL, credentials, and available operations
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2. An API client the orchestration script can call
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3. A mapping from the source's data model to what the agent expects (interview ID, date, interviewee, content, tags)
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Copy `notion.example.json` or `google-drive.example.json` as a starting point.
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If you build a connector for a new system, consider raising a PR back to the main pm-claude-skills repo.
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## Security notes
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**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.
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**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.
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**Rotate credentials periodically.** Both Notion integration tokens and Google service account keys can be regenerated. Do this every 90 days as a security practice.
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{
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"connector_name": "google-drive",
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"version": "1.0.0",
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"description": "Google Drive connector for the PM Discovery Agent. Reads interview notes from a Google Drive folder where each interview is a Google Doc.",
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"configuration": {
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"folder_id": "FOLDER_ID_HERE",
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"file_type": "application/vnd.google-apps.document",
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"include_subfolders": false,
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"expected_naming_convention": "YYYY-MM-DD - Interviewee Name.gdoc",
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"default_sort": {
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"field": "modifiedTime",
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"direction": "desc"
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},
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"default_filters": {
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"exclude_trashed": true,
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"min_word_count": 100
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},
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"rate_limit_requests_per_minute": 60
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},
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"credentials": {
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"_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.",
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"auth_method": "service_account",
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"service_account_key_path_env_var": "GOOGLE_APPLICATION_CREDENTIALS",
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"service_account_key_placeholder": "/path/to/service-account-key.json"
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},
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"available_operations": [
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{
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"name": "list_recent_documents",
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"description": "Get the N most recent Google Docs in the configured folder",
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"filters": ["modifiedAfter", "name_contains", "starred"],
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"max_results": 50
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},
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{
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"name": "get_document_content",
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"description": "Fetch the full text content of a specific Google Doc",
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"required_input": "file_id"
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},
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{
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"name": "search_documents",
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"description": "Search document content by keyword across the folder",
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"required_input": "search_query"
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}
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],
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"permissions_required": [
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"https://www.googleapis.com/auth/drive.readonly",
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"https://www.googleapis.com/auth/documents.readonly"
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],
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"_setup_instructions": [
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"1. Go to Google Cloud Console: https://console.cloud.google.com/",
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"2. Create a new project (or use existing) — name it something like 'PM Discovery Agent'",
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"3. Enable the Google Drive API and Google Docs API for the project",
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"4. Create a service account: IAM & Admin > Service Accounts > Create Service Account",
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"5. Download the service account key as JSON",
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"6. Save the JSON file to a secure location (e.g., ~/.config/pm-discovery-agent/service-account.json)",
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"7. Set the environment variable: export GOOGLE_APPLICATION_CREDENTIALS='/path/to/service-account.json'",
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"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)",
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"9. Share that folder with the service account email (it looks like xxx@your-project.iam.gserviceaccount.com) — give it Viewer access",
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"10. Update folder_id in this file",
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"11. Save this file as 'google-drive.json' (without the .example)",
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"12. Test the connection: bash orchestrate.sh --research-question 'Test' --interview-source google-drive --dry-run"
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],
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"_alternative_simpler_setup": [
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"If creating a service account feels heavy, you can use OAuth user credentials instead:",
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"1. Go to APIs & Services > Credentials in Google Cloud Console",
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"2. Create OAuth client ID > Desktop application",
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"3. Download the credentials JSON",
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"4. The first time the agent runs, it'll open a browser for you to authorise",
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"This is simpler but requires re-authorisation if the token expires."
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],
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"_folder_organisation_recommendation": [
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"If you're starting fresh, organise your interview notes folder like this:",
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"- One folder for the discovery project",
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"- One Google Doc per interview, named '2026-05-10 - Sarah Chen.gdoc' (date + interviewee)",
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"- Inside each doc: structured headers for Background, Notes, Key Quotes, Observations, Follow-ups",
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"Consistent structure makes the synthesis dramatically better."
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],
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"_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."
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}
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{
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"connector_name": "notion",
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"version": "1.0.0",
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"description": "Notion connector for the PM Discovery Agent. Reads interview notes from a Notion database where each interview is a database row.",
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"configuration": {
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"database_id": "DATABASE_ID_HERE",
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"workspace_url": "https://www.notion.so/your-workspace",
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"expected_properties": {
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"title_property": "Name",
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"date_property": "Interview Date",
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"interviewee_property": "Interviewee",
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"segment_property": "Segment",
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"status_property": "Status",
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"tags_property": "Tags"
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},
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"default_filters": {
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"status_is": "Completed",
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"exclude_archived": true
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},
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"default_sort": {
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"property": "Interview Date",
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"direction": "descending"
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},
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"rate_limit_requests_per_second": 3
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},
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"credentials": {
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"_comment": "Notion uses an integration token. Create one at https://www.notion.so/my-integrations and share your database with it.",
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"integration_token_env_var": "NOTION_INTEGRATION_TOKEN",
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"integration_token_placeholder": "secret_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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},
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"available_operations": [
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{
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"name": "list_recent_interviews",
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"description": "Get the N most recent interviews from the configured database",
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"filters": ["segment", "tags", "date_range", "status"],
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"max_results": 50
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},
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{
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"name": "get_interview_content",
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"description": "Fetch the full page content of a specific interview (notes, transcript, observations)",
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"required_input": "page_id"
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},
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{
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"name": "search_interviews",
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"description": "Search interview content by keyword",
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"required_input": "search_query"
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}
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],
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"permissions_required": [
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"Read content",
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"Read user information without email"
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],
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"_setup_instructions": [
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"1. Create a Notion integration at https://www.notion.so/my-integrations",
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"2. Click '+ New integration', name it 'PM Discovery Agent', leave defaults",
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"3. After creation, copy the Internal Integration Token (starts with 'secret_')",
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"4. Set the environment variable: export NOTION_INTEGRATION_TOKEN='secret_xxxxx...'",
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"5. Open your interview notes database in Notion",
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"6. Click '...' menu in top right > 'Add connections' > select your new integration",
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"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",
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"8. Update database_id in this file",
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"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)",
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"10. Save this file as 'notion.json' (without the .example)",
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"11. Test the connection: bash orchestrate.sh --research-question 'Test' --interview-source notion --dry-run"
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],
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"_notion_database_setup_recommendation": [
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"If you don't have a Notion database for interviews yet, create one with these properties:",
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"- Name (title) — interview identifier or interviewee name",
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"- Interview Date (date) — when the interview happened",
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"- Interviewee (text) — who was interviewed",
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"- Segment (select) — which user segment they belong to",
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"- Status (select) — Scheduled / Completed / Cancelled",
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"- Tags (multi-select) — research project, persona, or feature area",
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"Then write your interview notes in the page body."
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],
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"_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."
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}
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