Personal Commit Review

Write a short Markdown retrospective of a person's GitHub work. Make it read like a written review, not a changelog and not a bullet-only summary.

Default Behavior

• If the user does not specify a time period, default to the last 7 days and say so plainly.
• Default deliverable: one Markdown note, about one page total, usually 400-700 words.
• Use scripts only when they materially help. This skill is primarily a workflow for gathering evidence and writing well.

Workflow

1. Set the review window

• If the period is ambiguous, ask once. If asking would only slow down an otherwise straightforward request, default to the last 7 days and state the assumption.
• Prefer exact --since and --until dates for weekly, monthly, quarterly, or release reviews.
• Decide whether the user wants the review only in chat or also written to a Markdown file.

2. Gather the contribution map

• Start with GitHub totals and the touched repositories. This gives the frame of the review before you study individual commits.
• Manual gh usage is fine for v1 and should be the default for small review windows or a small number of repos.
• Use the helper script only when the time window or repo count makes manual collection annoying.

gh api graphql -f query='query {
  viewer {
    login
    contributionsCollection(from:"2026-03-01T00:00:00Z", to:"2026-03-07T23:59:59Z") {
      totalCommitContributions
      restrictedContributionsCount
      commitContributionsByRepository(maxRepositories:25) {
        repository {
          nameWithOwner
          description
          isPrivate
          url
          primaryLanguage { name }
        }
        contributions(first:7) {
          nodes { occurredAt commitCount }
        }
      }
    }
  }
}'

• If you want the helper path, use:

uv run .agents/skills/personal-commit-review/scripts/collect_commit_review.py \
  --since 2026-03-01 \
  --until 2026-03-07 \
  --output /tmp/commit-review.json \
  --brief-out /tmp/commit-review-brief.md

• Treat GitHub's contribution totals as authoritative counts and the retrieved commit objects as the visible research set.
• Open github-collection-notes.md when the data looks incomplete or the GitHub queries need adjustment.

3. Understand the repos before interpreting the commits

• Do not infer meaning from commit messages alone.
• For each repo that looks important, gather the minimum context needed to understand what the work was for:
  • repo description and primary language
  • README, architecture note, or docs if the repo has them
  • touched file paths and folder names
  • one or two neighboring commits if a headline is too vague
• Prefer understanding the product or subsystem before writing about what changed in it.

Useful commands:

gh repo view OWNER/REPO --json nameWithOwner,description,primaryLanguage,url
gh api --method GET repos/OWNER/REPO/commits -f author=USERNAME -f since=2026-03-01T00:00:00Z -f until=2026-03-07T23:59:59Z -f per_page=20
gh api --method GET repos/OWNER/REPO/commits/SHA

• Example: if a commit mentions Liquid Glass, verify whether the repo is a macOS app, which window or settings files changed, and whether the repo context supports that description.
• If the repo context is still unclear, describe the change more conservatively.

4. Pick the storylines

• Pick 2-4 themes for the review, not 10 separate commit bullets.
• Good themes are usually product-facing or architectural:
  • interface polish and design alignment
  • release and packaging work
  • infrastructure or tooling improvements
  • a feature thread that moved from idea to working implementation
• Support each theme with concrete evidence from commits, repo context, and changed paths.

5. Parallelize research when it actually helps

• If the review spans many repos or many strong highlights, split follow-up work by repo or theme.
• Give each subagent exclusive ownership of specific repos or highlight commits.
• Do not have every subagent repeat the full discovery step.
• Keep the main agent responsible for the final narrative voice and the final fact check.

6. Write the review as prose

• Use the default structure in output-template.md.
• Do not return a wall of paragraphs. The final Markdown should read like a compact report.
• Start with a short framing paragraph that includes the key stats: commit count, repo count, major languages, and any caveat that materially changes interpretation.
• Include a small stats overview table near the top.
• Include a repository overview table with Markdown links to the repos when GitHub exposed the repo URLs.
• Then write 2-3 short body sections that tell the story of the week.
• Name specific repos and changes inside the prose. Example style: "trnscrb moved closer to native macOS conventions, with settings-window work explicitly calling out HIG and Liquid Glass patterns."
• Mention 3-5 standout changes, but weave them into the text instead of turning them into a checklist.
• Include 2-4 linked highlights near the end, pointing to repos or commits where that helps the report feel concrete.
• Keep the whole review to about one page total.
• End with one compact caveat note only if needed: restricted contributions, incomplete visibility, inaccessible repos, or uncertain attribution.

Troubleshooting

• Only verify GitHub access if the data collection step fails or returns clearly wrong results.

gh auth status
gh api rate_limit

• Do not require extra GitHub scopes by default.
• Open github-collection-notes.md if the contribution totals and visible commit set do not line up cleanly.

Output Standard

• Prefer Markdown if writing to a file.
• Keep the tone reflective and concrete.
• Use stats to anchor the story, not to dominate it.
• Use report structure: heading, one-line deck, stats table, repository table, prose sections, compact highlights.
• Link repo names with standard Markdown links whenever the repo URL is known, including private repos that were explicitly surfaced by the authenticated GitHub query.
• Avoid raw commit dumps, long bullet lists, or one-sentence-per-commit writing.
• Avoid filling the whole page with caveats. The caveat note should stay short unless the data is genuinely unusable.

Anti-Patterns

• Do not treat the helper script as mandatory.
• Do not brute-force every accessible repository when a few repos clearly dominate the review.
• Do not claim details for restricted contributions. Say they exist, not what they were.
• Do not require gh auth refresh -s user unless the user explicitly wants deeper email-based matching.
• Do not write from commit headlines alone if the repo context is available.
• Do not paste raw JSON or raw API dumps into the final review.
• Do not omit repo links and stats when the data is available.

Resources

• references/output-template.md Default Markdown structure for the final review.
• scripts/collect_commit_review.py Optional helper for broad repo discovery and compact briefing when manual collection is too slow.
• references/github-collection-notes.md Open when debugging data gaps, tuning limits, or changing the GitHub collection strategy.