Investigating repository history
Skill CodeAlive-AI/ai-driven-development/skills/investigating-repository-history
Investigate GitHub repository history before risky code changes using git blame/log, GitHub PRs, review comments, squash/rebase/cherry-pick/rename heuristics, and cited evidence. Use when asking why code exists, whether a change is safe, what PR introduced behavior, or before editing API, compatibility, security, concurrency, persistence, migration, or performance-sensitive code.From its SKILL.md
npx -y skills add CodeAlive-AI/ai-driven-development --skill investigating-repository-historyAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- runs commandsInstructs the agent to run 6 commands, including `python3 scripts/history_context.py inspect --repo-dir /path/to/repo --path path/to/file.ext --start 120 --end 160 --question "Can I remove this constraint?" --format markdown` and 5 more.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
7.7 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it
Repository History Investigator
Use this skill to reconstruct the historical intent behind code before changing it. The goal is not merely “find the blame commit”; the goal is to return a compact, cited history note explaining relevant PRs, review comments, constraints, rejected approaches, and anomalies.
Contents
- Trigger conditions
- Core rule
- Fast path
- Progressive disclosure
- Investigation workflow
- Evidence confidence rules
- Output template
- Gotchas
- Available scripts
Trigger conditions
Use this skill when the user asks any of these:
- “Why is this code written this way?”
- “Can I remove/simplify/change this check, constraint, branch, migration, public API, or feature flag?”
- “Which PR introduced this behavior or regression?”
- “Find the relevant PR/review discussion/history for this code.”
- Before editing code that touches API compatibility, security, concurrency, persistence, migrations, performance, generated interfaces, feature flags, or unclear legacy/workaround logic.
Do not use this skill for trivial new code with no dependency on existing behavior.
Core rule
Before making a risky edit, produce a history note answering:
- What code scope was inspected?
- Which commits and PRs are relevant?
- Which review comments or PR discussions explain intent?
- What constraints, risks, rejected approaches, or tests were found?
- Is the evidence strong, weak, contradictory, stale, truncated, or unknown?
- How should the implementation plan change?
If the evidence is weak, say UNKNOWN and lower confidence. Never invent intent from a semantic match alone.
Fast path
From the repository working tree, run the collector first. If the skill directory is not the current directory, prefix the script path with the installed skill path and pass --repo-dir /path/to/repo.
python3 scripts/history_context.py inspect \
--repo-dir /path/to/repo \
--path path/to/file.ext \
--start 120 --end 160 \
--question "Can I remove this constraint?" \
--format markdown
For symbol-level questions without exact lines:
python3 scripts/history_context.py inspect \
--repo-dir /path/to/repo \
--path path/to/file.ext \
--symbol SymbolOrFunctionName \
--question "Why does this behavior exist?" \
--format markdown
For JSON suitable for deeper agent reasoning:
python3 scripts/history_context.py inspect \
--repo-dir /path/to/repo \
--path path/to/file.ext \
--start 120 --end 160 \
--symbol SymbolOrFunctionName \
--question "What PR introduced this behavior?" \
--format json \
--output history-context.json
Then read only the relevant sections of the output. Do not paste huge raw PR/comment dumps into the final answer.
Progressive disclosure
Load these files only when needed:
references/ANOMALIES.md— use when exact commit→PR mapping fails, or when squash, rebase, cherry-pick, backport, revert, rename, split, generated files, or mass refactors are possible.references/GH_CLI.md— use when the script fails or manualgh apicalls are needed.references/DECISION_ATOMS.md— use when converting PR/comment evidence into constraints, risks, rejected approaches, or test requirements.references/OUTPUT_SCHEMA.md— use when producing a formal machine-readable report.references/EVALUATION.md— use when testing or improving the skill.
Investigation workflow
- Define scope. Identify paths, line ranges, symbols, tests, error strings, feature flags, and any proposed diff.
- Collect local history. Use the script or manual
git blame -w -M -C -C -C,git log --follow,git log -S, andgit log -G. - Map commits to PRs. Prefer exact GitHub commit→PR association. Treat it as one signal, not the entire answer.
- Fetch PR evidence. For candidate PRs, inspect PR body, files, commits, reviews, inline review comments, and issue comments.
- Resolve anomalies. If mapping is weak, apply the Provenance Mesh: commit association + patch equivalence + content/symbol lineage.
- Extract decision atoms. Convert evidence into explicit claims: constraints, compatibility requirements, security invariants, performance constraints, rejected approaches, test requirements.
- Assess risk. Downgrade confidence for semantic-only matches, path-only matches, reverted PRs, API truncation, large PRs, generated files, or missing PRs.
- Produce a history note before editing code.
Evidence confidence rules
High confidence:
- exact GitHub commit→PR association; or
- patch/hunk equivalence plus path/symbol agreement; or
- review comment remaps to the current hunk/symbol and matches the proposed change.
Medium confidence:
- same symbol/path plus relevant PR discussion, but no patch-level match.
Low confidence:
- semantic search only, title/body match only, path-only match, or stale/reverted evidence.
Never claim “this was decided” unless a commit, PR body, review, review comment, issue comment, or linked issue supports it.
Output template
Use this concise template in the final answer or implementation plan:
## History note
Scope inspected: [paths, lines, symbols]
Relevant evidence:
- PR #[n] — [relation: exact/squash-like/rename-lineage/search], [why relevant], [confidence]
- Commit [sha] — [what it changed], [relation]
- Review/comment — [constraint or concern]
Decision atoms:
- [constraint/risk/rejected approach/test requirement] — [claim] — evidence: [PR/comment/commit]
Risk: [low|medium|high|unknown]
Confidence: [0.00-1.00]
Unknowns/truncation: [none or list]
Plan impact: [proceed|modify plan|ask human|do not change]
Gotchas
git blameis a seed generator, not truth. Formatting commits, moves, squashes, and refactors can hide origin.- A PR can be relevant even if it did not introduce the current line; review comments may explain why an alternative was rejected.
- Squash merges often require patch/hunk matching because the final commit SHA differs from PR commits.
- File paths are not identity. Track file lineage, directory moves, symbol fingerprints, and hunk context.
- Reverted PRs are stale evidence unless a later PR reintroduced the same decision.
- Large
gh apiresponses may be truncated by the underlying GitHub endpoints. If truncation is possible, mark evidence incomplete. - General PR conversation comments come from issue comments; inline review comments come from PR review comments.
Available scripts
scripts/history_context.py— main collector for local Git + GitHub PR evidence. Runpython3 scripts/history_context.py --help.scripts/compact_pr.py— fetch one or more PRs and print compact evidence. Runpython3 scripts/compact_pr.py --help.scripts/validate_skill.py— validate this skill’s frontmatter and basic structure.
What ships with it: 14 files
77.9 KB alongside SKILL.md, 5 of them executable
agents/
- openai.yaml374 B
assets/
references/
- ANOMALIES.md4.5 KB
- DECISION_ATOMS.md1.8 KB
- EVALUATION.md1.1 KB
- GH_CLI.md3.4 KB
- OUTPUT_SCHEMA.md1.9 KB
scripts/
- compact_pr.pyruns6.0 KB
- history_context.pyruns42.8 KB
- validate_skill.pyruns2.9 KB
tests/
- __init__.pyruns0 B
- test_skill.pyruns10.0 KB
Gives 0 of the 12 instructions most pr commit review skills give in ~1.6k tokens
Counted across 1,055 of the 1,911 authors here whose files we hold, read 2026-09-06
- Use conventional commit message formatin 150 of 1055, across 145 files
- Announce skill usage at startin 78 of 1055
- Use imperative mood for commit descriptionsin 54 of 1055, across 51 files
- Add directory to gitignore if not ignoredin 52 of 1055, across 41 files
- Use imperative mood for commit subjectin 52 of 1055
- Run tests to verify clean baselinein 42 of 1055, across 32 files
- Push branch to originin 40 of 1055, across 38 files
- Verify worktree directory is ignored before creationin 39 of 1055, across 32 files
- Delete branches after mergingin 38 of 1055, across 30 files
- Create worktree with new branchin 37 of 1055, across 32 files
- Wrap body text at 72 charactersin 36 of 1055, across 34 files
- Auto-detect and run project setupin 35 of 1055, across 27 files
Said here and by no other author read
- produce a history note before making risky edits
- map commits to pull requests using evidence
- extract constraints and rejected approaches from discussions
- assess evidence confidence for all findings
- use git blame and log to collect local history
- inspect pull request bodies and review comments
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.