commit-surgeon
Skill0 starsChanged 4 months agoMITView on GitHub
Split a messy working tree with several unrelated changes into a clean, reviewable sequence of atomic commits, each with an inferred Conventional Commit message. Use this when the user has a pile of uncommitted work spanning multiple concerns and wants it committed sensibly, asks to "split / organize / clean up my changes / commits", wants "atomic commits" or "one commit per concern", or is preparing a tidy PR history. Triggers on: "split my changes", "atomic commits", "organize commits", "my working tree is a mess", "commit this properly", "conventional commits", "separate these changes".
1 other project uses a version of this.
Adopted by
Most recently taken up by
- eeshsaxena/agent-skillstheir own version, first seen Aug 5, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- eeshsaxena/agent-skills★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- blast-radiusSkill
- repo-radarSkill
- session-handoffSkill
- stack-to-reproSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 83
Commit order is chosen for reviewability: build → refactor → feat → fix → perf → test → docs → ci → style → chore, so structural changes …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Commit Surgeon
What this does
Big, mixed commits are where code review goes to die — a reviewer can't approve a bug fix without also vetting the unrelated refactor and doc tweak riding along. This skill reads your working tree, groups the changes by concern, proposes an ordered set of atomic commits with sensible Conventional-Commit messages, and hands you a script to apply them. Clean history, faster review, easier reverts — without you hand-staging file by file.
When to use it
- The user has accumulated unrelated changes and wants them committed cleanly.
- The user asks to split / organize / tidy commits, or wants "atomic commits".
- You're about to open a PR and the history is one undifferentiated blob.
Workflow
1. Plan the split
python3 skills/commit-surgeon/scripts/plan_commits.py --md commit-plan.md --sh commit.shThis inspects tracked and untracked changes, clusters files by concern
(src / test / docs / config / ci / style) and by module, infers a commit type
(feat, fix, refactor, perf, docs, test, build, ci, style,
chore) from file type and change keywords, and writes:
commit-plan.md— the proposed commits, in review order, andcommit.sh— a runnable staging+commit script.
It is read-only; nothing is committed until you act.
2. Review the plan with the user — this is the important step
Present the proposed commits. The type/scope/message are inferred heuristics;
correct them where the intent is wrong (only you and the user know that the
"refactor" was actually the bug fix). Pay special attention to any ⚠️
mixed-concern files: a single file carrying both a feature and a fix should be
split with git add -p so each hunk lands in the right commit — do that
manually rather than through the file-level script.
3. Apply
Either run the generated script:
bash commit.sh…or, when files are mixed, stage hunk-by-hunk yourself (git add -p) following
the plan's grouping, committing each concern with its message. Refine any
message before committing — never ship an inferred subject you haven't read.
4. Verify the history
git log --oneline --statConfirm each commit is self-contained (builds/tests would pass at that commit if
practical) and that no unrelated change leaked across a boundary. Reorder or
git commit --amend/git rebase -i if needed.
Conventions
- Messages follow Conventional Commits (
type(scope): subject). Scope is the module directory; it's omitted for root-level changes. - Commit order is chosen for reviewability:
build → refactor → feat → fix → perf → test → docs → ci → style → chore, so structural changes land before the features that use them. - A feature and its tests in the same module are grouped into one commit by design — an atomic commit includes its own tests.
Notes & limits
- Grouping is at file granularity, which is safe and reversible. True
hunk-level splitting (two concerns in one file) is flagged, not automated —
use
git add -pthere. - Inference is keyword/heuristic based; it cannot read intent. Always review types and messages before committing.
- The generated script runs
git resetfirst to unstage everything, then stages each group cleanly. Read it before running.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

