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GitHub Playbook
This repository can get more leverage from GitHub without adding much process overhead.
ai agent rag workflow
View sourceGitHub Playbook
This repository can get more leverage from GitHub without adding much process overhead.
Releases
Recommended release shape:
- tag a semantic version
- publish binaries through the existing GitHub Actions workflow
- keep a short manual changelog entry in
CHANGELOG.md - use GitHub release notes for a concise "why it matters" summary
Suggested release note structure:
- What changed
- Why it matters
- How to try it
Discussions
Suggested categories to enable in the GitHub UI:
- General
- Ideas
- Show and tell
- Q&A
Suggested starter discussion topics:
- How are you using context-pack with coding agents?
- What signals matter most in older or messy repositories?
- Where does first-pass briefing still fail?
Issues
Use issues for actionable engineering work:
- bugs in selection, ranking, or rendering
- feature requests tied to a concrete workflow problem
- measurable quality improvements
Good issue examples:
- Improve entrypoint detection in Python service repos
- Measure token savings on large unfamiliar repositories
- Add memory bootstrapping for learned repo notes
Labels
Recommended lightweight label set:
bugenhancementdocumentationbriefingheuristicsmemoryworkflowbreaking-change
Current Recommendation
If only a few GitHub features get active attention, prioritize these:
- Releases with clear notes
- Discussions for workflow feedback
- Issues tied to measurable product improvements
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