review-local-repo
Skill1 starsChanged 4 months agoApache-2.0View on GitHub
Review the local repository — structure, recent changes, and risks — read-only.
In this repository8 other files it gives its agents.
- check-logsSkill
- deployment-statusSkill
- deploy-serviceSkill
- investigate-outageSkill
- provision-supabaseSkill
- restart-serviceSkill
- rollback-deploySkill
- set-env-varsSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
Read-only review. Do not modify files.
≈ “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
When to use
The operator asks for a code/repo review, "what changed", a risk read, or a summary of the local project ("review this repo", "what's risky here").
Steps
- Map the repo (tree) and read the key entry points and changed files.
- For "what changed", inspect recent commits / the working diff.
- Report: structure, notable modules, recent changes, and concrete risks (untested paths, secrets, broken contracts) with file references.
- Propose follow-ups (tests, fixes) as suggestions — implementing them is a separate explicit request.
Readonly tools
- repo_tree / repo_read / repo_search
Governance
Read-only review. Do not modify files; any edit is a separate explicit, governed action. Never echo secrets found in the repo.
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.