121 lines
4.4 KiB
Markdown
121 lines
4.4 KiB
Markdown
---
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description: Analyze, categorize, and prioritize a batch of feature requests from customers or stakeholders
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argument-hint: "<feature requests as text, file, or paste>"
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---
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# /triage-requests -- Feature Request Triage
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Take a pile of feature requests — from support tickets, sales calls, surveys, or Slack — and turn them into a prioritized, actionable backlog.
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## Invocation
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```
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/triage-requests # asks for input
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/triage-requests [paste a list of requests]
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/triage-requests [upload a CSV/spreadsheet]
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```
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## Workflow
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### Step 1: Accept Feature Requests
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Accept requests in any format:
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- **Pasted text**: List of requests, one per line or paragraph
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- **Uploaded file**: CSV, Excel, or text file with request data
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- **Structured data**: If the input has columns (requester, request, date, etc.), preserve them
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If no input is provided, ask the user to paste or upload their feature requests.
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Parse each request to extract:
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- The core ask (what the user wants)
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- Context (who asked, when, why — if available)
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- Frequency signals (how many people asked for similar things)
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### Step 2: Gather Prioritization Context
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Ask the user (conversationally, not all at once):
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- What is the product? What stage is it in?
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- What are the current strategic goals or OKRs? (helps assess alignment)
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- Any constraints to consider? (team size, technical debt, upcoming deadlines)
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- Are there segments whose requests should carry more weight? (enterprise, churning users, power users)
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### Step 3: Categorize and Analyze
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Apply the **analyze-feature-requests** skill:
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- **Theme clustering**: Group similar requests into themes (e.g., "reporting & analytics", "collaboration", "mobile experience")
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- **Request count per theme**: How many unique requests map to each theme
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- **Strategic alignment**: Rate each theme against stated goals (High/Medium/Low/None)
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- **Segment analysis**: Which user segments are driving which themes
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- **Sentiment signals**: Are requests accompanied by frustration, churn threats, or delight?
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### Step 4: Prioritize
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Apply the **prioritize-features** skill:
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For each theme (and the top individual requests within each theme):
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| Factor | Assessment |
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|--------|-----------|
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| **Impact** | How many users affected? How severely? |
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| **Strategic alignment** | Does it serve current goals? |
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| **Effort estimate** | T-shirt size (S/M/L/XL) |
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| **Risk** | What happens if we don't do this? |
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| **Revenue signal** | Is this tied to deals, retention, or expansion? |
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Rank themes and produce a prioritized list.
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### Step 5: Generate Triage Report
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```
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## Feature Request Triage Report
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**Date**: [today]
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**Requests analyzed**: [count]
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**Themes identified**: [count]
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### Theme Summary
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| # | Theme | Requests | Top Ask | Alignment | Impact | Effort | Priority |
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|---|-------|----------|---------|-----------|--------|--------|----------|
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### Priority 1: Act Now
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[Themes/requests to include in near-term planning]
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- **[Theme]**: [X] requests — [why it's urgent]
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- Top requests: [list]
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- Recommended action: [build / prototype / investigate]
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### Priority 2: Plan Next
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[Themes worth planning but not urgent]
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### Priority 3: Collect More Signal
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[Themes with potential but insufficient evidence]
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### Priority 4: Decline or Defer
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[Requests that don't align with strategy — with rationale]
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### Notable Individual Requests
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[High-value one-off requests that didn't cluster into themes]
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### Patterns and Insights
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- [Key insight about what users are telling you]
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- [Segment-specific patterns]
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- [Gaps between what users ask for and underlying needs]
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```
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Save the report as a markdown file to the user's workspace.
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### Step 6: Offer Next Steps
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- "Want me to **create user stories** for the top-priority items?"
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- "Should I **brainstorm solutions** for any of these themes?"
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- "Want me to **design experiments** to validate demand before building?"
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- "Should I **draft a stakeholder update** summarizing this analysis?"
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## Notes
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- If the user provides a CSV with columns, preserve the data structure and enrich it
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- Look for the need behind the request — "add dark mode" might really mean "reduce eye strain during long sessions"
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- Flag requests that conflict with each other (e.g., "simplify the UI" vs. "add more configuration options")
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- If request volume is large (50+), summarize themes first and offer to drill into specific themes on request
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- Output the enriched data as a downloadable CSV if the input was structured data
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