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Launch metrics
How we measure understanding, activation, use, contribution, and retention for ecosystem launch.
Launch metrics distinguish attention from successful use. Vanity stars alone are not success.
Source of truth for the metric definitions: docs/ecosystem/launch/launch-package.json.
#Dimensions
| ID | Question | Initial target |
|---|---|---|
understanding | Can a visitor name each productβs role? | β₯ 90% in a lightweight user test |
activation | Do declared executable demos succeed cleanly? | 100% of executable demos in the launch package |
use | Do people complete a primary docs quickstart? | Baseline, then improve |
contribution | Do starter issues include setup + test instructions? | 100% of curated starters |
retention | Are showcase/recipe submissions reviewed within SLA? | First response β€ 2 business days |
#How we collect
- Docs / community analytics β product page funnels (privacy-preserving)
- Launch package gate β
pnpm check:launch-packagefor demo integrity - GitHub β issues, PRs, labels (
good first issue, community submissions) - Generated claims β public numeric claims only from
ecosystem-claims.json
#What we refuse to report
- Hand-typed package/agent counts that disagree with generated claims
- βStableβ claims for alpha surfaces
- Engagement metrics without a path back to a real demo or contribution
#Related
Explore nearby
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- PeerNewcomer journey
Understand the AgentsKit ecosystem, run a verified demo, and choose a contribution path without private guidance.
- PeerGood first issues
Curated issues ready to grab. Pick one, comment on it to claim, and ship a PR.