---
name: ds-contributor-health
description: Track contribution activity across teams — who's contributing, velocity trends, and early warning signs of disengagement.
user-invocable: true
---

# DS Contributor Health

Read [context/ds-context-guide.md](../context/ds-context-guide.md) for environment detection and configuration.
Read [context/output-patterns.md](../context/output-patterns.md) for output conventions.

## Purpose

Track contribution patterns across teams: who's contributing, what types, velocity trends, and early warning signs of disengagement (teams that stopped contributing, rising workaround signals).

## Input

`$ARGUMENTS` = optional time period or team focus. Default: last 90 days, all teams.

## Methodology

1. **Gather contribution data:**
   - GitHub MCP: PRs to DS repos, contributors, frequency, types of changes
   - Linear MCP: DS issues created by external teams, feature requests, bug reports
   - If none available, note that contribution data sources are unavailable; report which dimensions cannot be assessed

2. **Analyze patterns:**
   - **Active contributors**: teams/individuals with recent contributions
   - **Contribution types**: fixes vs. enhancements vs. new features (Curtis taxonomy)
   - **Velocity**: is contribution activity increasing, stable, or declining?
   - **New contributors**: teams contributing for the first time (onboarding signal)
   - **Churned contributors**: teams that used to contribute but stopped (disengagement signal)

3. **Identify warning signs:**
   - Teams that stopped contributing but are still actively shipping product (may be routing around the DS)
   - Increasing bug reports without corresponding fixes (friction signal)
   - Feature requests that go unanswered (trust erosion)

4. **Identify strengths:**
   - High-trust contributors who could mentor new teams
   - Contribution patterns that work well and should be replicated

## Output

Follow the report template from output-patterns.md. Include contributor summary, velocity trends, warning signs, and recommendations for improving contributor health.
- Executive summary: 3-5 sentences max
- Limit to top 5 metrics and top 3 recommendations
- Each recommendation: 1-2 sentences with rationale