commit
Skill431 starsChanged 8 months agoMITView on GitHub
Stage and commit changes with a well-formed commit message following the WikiEduDashboard format. Use this skill when asked to commit, make a commit, or create a commit.
187 other projects use a version of this.
Adopted by
Most recently taken up by
- yagizdo/quivertheir own version, first seen Nov 15, 2026
- markmhendrickson/neotomatheir own version, first seen Nov 15, 2026
- ShipfoxHQ/shipfoxtheir own version, first seen Nov 15, 2026
- atomicinnovation/acceleratortheir own version, first seen Nov 14, 2026
- Integralist/agent-skillstheir own version, first seen Nov 14, 2026
- gtapps/claude-code-hermittheir own version, first seen Nov 13, 2026
Used with
Projects with it also use validate-plan, act-on-feedback and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
shawn-dumasSkillvalidate-plan
Validate an orchestration plan after pre-flight certification. Runs adversarial review, deep review (verify prompt data against codebase), and PoC gate for risky approaches. Auto-invoked by orchestrate-* skills at Step 8.
Also in 5 projects that use this
MicrosoftSkillact-on-feedback
Act on user feedback attached to the current session. Use when the user submits feedback on the session's changes via the Submit Feedback button.
Also in 3 projects that use this
decocmsSkilladd-mcp-tools
Guide for adding new MCP tools with consistent patterns for schemas, tool definitions, registry updates, and Better Auth integration
Also in 3 projects that use this
MicrosoftSkillgenerate-run-commands
Generate or modify run commands for the current session. Use when the user wants to set up or update run commands that appear in the session's Run button.
Also in 3 projects that use this
mitsuhikoSkilloebb-scotty
Austrian rail travel planner (ÖBB Scotty). Use when planning train journeys in Austria, checking departures/arrivals at stations, or looking for service disruptions. Covers ÖBB trains, S-Bahn, regional trains, and connections to neighboring countries.
Also in 3 projects that use this
mitsuhikoSkillpi-share
Load and parse session transcripts from shittycodingagent.ai/buildwithpi.ai/buildwithpi.com/pi.dev (pi-share) URLs. Fetches gists, decodes embedded session data, and extracts conversation history.
Also in 3 projects that use this
Other versions187 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 187
- microsoft/vscode★ 195ksame name
- TryGhost/Ghost★ 56ksame name
- ToolJet/ToolJet★ 41ksame name
- ShareX/ShareX★ 41ksame name
- openai/symphony★ 27ksame name
- ryoppippi/ccusage★ 19ksame name
- ccusage/ccusage★ 19ksame name
- windmill-labs/windmill★ 19ksame name
- EverMind-AI/EverMemOS★ 14ksame name
- EverMind-AI/EverOS★ 14ksame name
177 more not listed
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 repository7 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- course-update-reconSkill
- feature-specSkill
- google-doc-change-requestsSkill
- prepare-prSkill
- review-prSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 4 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 167 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Create a git commit with a message that follows the project's format.
- Very specific: line 10
Use the current coding agent's actual product name in attribution text (for example, Claude Code or Codex).
- Distinctive: line 22
Follow the project format exactly:
- Distinctive: line 55
Call out non-obvious decisions or tradeoffs
- Distinctive: line 56
Keep it factual; don't pad
- Very specific: line 110
After committing, confirm success with git log -1 --format="%h %s".
“Common” is measured: kept by at least 6 in 10 of the 167 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Commit
Create a git commit with a message that follows the project's format.
Use the current coding agent's actual product name in attribution text (for
example, Claude Code or Codex). Never attribute one agent's work to another.
Phase 1: Understand what's being committed
git status— identify staged and unstaged filesgit diff --staged— read every staged change in detailgit diff— note any unstaged changes (do not commit these unless asked)- Review the conversation history — what was the user trying to accomplish, and why?
Phase 2: Draft the commit message
Follow the project format exactly:
<Subject line: imperative mood, ≤72 chars>
## Changes
<What was built or changed and why, organized by file or component.
Include any non-obvious design decisions or tradeoffs.>
## Process
<How the current coding agent was used: what the user asked for, what approach
was taken, and any errors or corrections along the way. Be candid and specific
— if the agent got something wrong and needed correction, say so. If the
solution was straightforward, say that too.>
(Commit message written by <agent name>.)
Co-Authored-By: <current agent's trailer, per the harness/environment instructions>Subject line guidelines
- Imperative mood: "Fix flaky spec" not "Fixed" or "Fixes"
- ≤72 characters
- No trailing period
- Specific enough to understand without reading the body
Changes section guidelines
- Organize by file or logical component
- Explain why, not just what — the diff already shows what changed
- Call out non-obvious decisions or tradeoffs
- Keep it factual; don't pad
Process section guidelines
Describe the actual back-and-forth, then include a session summary paragraph covering the following. Be specific with numbers where you can; estimate and note the uncertainty where you can't.
Session provenance — Did this session start from scratch, or were the changes already partially or fully written before the session began? If the user brought in pre-existing code or commits, say so and characterize how much of the work predates this conversation.
Prompts and human input — How many messages did the user send? Roughly how much text did they write in total (a few words, a sentence or two per message, paragraph-length)? Was the direction terse or detailed?
Session length and character — Was this a short focused exchange (a handful of turns) or an extended back-and-forth (many turns, multiple approaches tried)? Did the work require iteration and correction, or was it resolved quickly?
Tests run — How many test runs happened over the course of the session, and what was the outcome trajectory (e.g. "two failures before a clean pass", "green on the first run")?
Tokens — If token usage is visible in the current agent's UI, report it. Otherwise omit this entirely.
This section exists so future readers can calibrate how much human direction and iteration went into the work. Make it genuinely informative, not boilerplate.
Phase 3: Commit
Stage files if needed, then commit using a HEREDOC to preserve formatting:
git commit -m "$(cat <<'EOF'
Subject line here
## Changes
...
## Process
...
(Commit message written by <agent name>.)
Co-Authored-By: <current agent's trailer, per the harness/environment instructions>
EOF
)"After committing, confirm success with git log -1 --format="%h %s".
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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.

