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GitHub Playbook

This repository can get more leverage from GitHub without adding much process overhead.

May 2, 2026
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ai agent rag workflow
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GitHub 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:

  1. What changed
  2. Why it matters
  3. 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:

  • bug
  • enhancement
  • documentation
  • briefing
  • heuristics
  • memory
  • workflow
  • breaking-change

Current Recommendation

If only a few GitHub features get active attention, prioritize these:

  1. Releases with clear notes
  2. Discussions for workflow feedback
  3. Issues tied to measurable product improvements

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