requesting-review
Skill0 starsChanged 46 days agoMITView on GitHub
Use when substantial or risky work is complete, before merging, or when a second perspective would catch what you might have missed
2 other projects use a version of this.
Adopted by
Most recently taken up by
- ali-sheiba/development-workflowtheir own version, first seen Oct 25, 2026
- renathoaz/arsyntheir own version, first seen Mar 24, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- renathoaz/arsyn★ 2same name
- ali-sheiba/development-workflow★ 1same 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 repository13 other files it gives its agents.
- debugging-systematicallySkill
- delegating-to-subagentsSkill
- executing-plansSkill
- finishing-workSkill
- investigating-in-parallelSkill
- isolating-workspacesSkill
- planning-workSkill
- receiving-reviewSkill
- shaping-designsSkill
- testing-firstSkill
- using-tackleSkill
- verifying-before-claimingSkill
- writing-skillsSkill
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 12
Trivial / Small: no separate review. Read your own diff once before reporting.
≈ “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
Requesting Review
A reviewer with fresh context sees what the author has stopped seeing. Review supplements deterministic checks (tests, types, linters) but doesn't replace them: run those first, so the reviewer spends attention on what machines can't judge.
Scale it
- Trivial / Small: no separate review. Read your own diff once before reporting.
- Substantial: one review of the whole change.
- Risky (security, data, money, public API, hard to undo): review, and verify each serious finding.
How
- Run the deterministic checks first and fix what they find.
- Gather context for the reviewer: what was meant to be built (spec or task text), what was built, and the change range (commit SHAs or a list of files). Give it only this, not your session history.
- Dispatch a reviewer with
reviewer-prompt.md. Use a capable model for risky changes. If the harness can't dispatch subagents, do a separate review pass yourself using the prompt as a checklist, reading the diff rather than your memory of it, or ask the user to review. - Verify findings before acting. For each Critical or Important finding, confirm it against the code: reproduce it, or read the lines cited. Reviewers are sometimes wrong, especially without full context.
- Act by severity:
- Critical: fix before anything else.
- Important: fix before merging, or explain to the user why not.
- Minor: fix if cheap; otherwise list it.
- Re-review only what changed, and only if the fixes were non-trivial. Loops end when checks pass and serious findings are resolved, not when a reviewer says "approved".
Skip or shorten when
- The user will review the change themselves and would rather do that.
- The change is mechanical (rename, formatting, dependency bump) and the checks pass.
Done means
Deterministic checks pass, and every verified Critical or Important finding is fixed or explicitly accepted by the user.
Next
receiving-reviewfor handling the feedbackfinishing-work
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.

