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description: Analyze, categorize, and prioritize a batch of feature requests from customers or stakeholders argument-hint: "<feature requests as text, file, or paste>"

/triage-requests -- Feature Request Triage

Take a pile of feature requests — from support tickets, sales calls, surveys, or Slack — and turn them into a prioritized, actionable backlog.

Invocation

/triage-requests                           # asks for input
/triage-requests [paste a list of requests]
/triage-requests [upload a CSV/spreadsheet]

Workflow

Step 1: Accept Feature Requests

Accept requests in any format:

• Pasted text: List of requests, one per line or paragraph
• Uploaded file: CSV, Excel, or text file with request data
• Structured data: If the input has columns (requester, request, date, etc.), preserve them

If no input is provided, ask the user to paste or upload their feature requests.

Parse each request to extract:

• The core ask (what the user wants)
• Context (who asked, when, why — if available)
• Frequency signals (how many people asked for similar things)

Step 2: Gather Prioritization Context

Ask the user (conversationally, not all at once):

• What is the product? What stage is it in?
• What are the current strategic goals or OKRs? (helps assess alignment)
• Any constraints to consider? (team size, technical debt, upcoming deadlines)
• Are there segments whose requests should carry more weight? (enterprise, churning users, power users)

Step 3: Categorize and Analyze

Apply the analyze-feature-requests skill:

• Theme clustering: Group similar requests into themes (e.g., "reporting & analytics", "collaboration", "mobile experience")
• Request count per theme: How many unique requests map to each theme
• Strategic alignment: Rate each theme against stated goals (High/Medium/Low/None)
• Segment analysis: Which user segments are driving which themes
• Sentiment signals: Are requests accompanied by frustration, churn threats, or delight?

Step 4: Prioritize

Apply the prioritize-features skill:

For each theme (and the top individual requests within each theme):

Factor	Assessment
Impact	How many users affected? How severely?
Strategic alignment	Does it serve current goals?
Effort estimate	T-shirt size (S/M/L/XL)
Risk	What happens if we don't do this?
Revenue signal	Is this tied to deals, retention, or expansion?

Rank themes and produce a prioritized list.

Step 5: Generate Triage Report

## Feature Request Triage Report

**Date**: [today]
**Requests analyzed**: [count]
**Themes identified**: [count]

### Theme Summary
| # | Theme | Requests | Top Ask | Alignment | Impact | Effort | Priority |
|---|-------|----------|---------|-----------|--------|--------|----------|

### Priority 1: Act Now
[Themes/requests to include in near-term planning]
- **[Theme]**: [X] requests — [why it's urgent]
  - Top requests: [list]
  - Recommended action: [build / prototype / investigate]

### Priority 2: Plan Next
[Themes worth planning but not urgent]

### Priority 3: Collect More Signal
[Themes with potential but insufficient evidence]

### Priority 4: Decline or Defer
[Requests that don't align with strategy — with rationale]

### Notable Individual Requests
[High-value one-off requests that didn't cluster into themes]

### Patterns and Insights
- [Key insight about what users are telling you]
- [Segment-specific patterns]
- [Gaps between what users ask for and underlying needs]

Save the report as a markdown file to the user's workspace.

Step 6: Offer Next Steps

• "Want me to create user stories for the top-priority items?"
• "Should I brainstorm solutions for any of these themes?"
• "Want me to design experiments to validate demand before building?"
• "Should I draft a stakeholder update summarizing this analysis?"

Notes

• If the user provides a CSV with columns, preserve the data structure and enrich it
• Look for the need behind the request — "add dark mode" might really mean "reduce eye strain during long sessions"
• Flag requests that conflict with each other (e.g., "simplify the UI" vs. "add more configuration options")
• If request volume is large (50+), summarize themes first and offer to drill into specific themes on request
• Output the enriched data as a downloadable CSV if the input was structured data