review-panel
Skill3 starsChanged 4 months agoMITView on GitHub
Use when any substantive work product has been generated — copy, emails, documents, proposals, plans, code, designs, skills, newsletters — and is about to be delivered, shipped, marked done, or given a quality verdict. Also use when the user asks for a review or critique of existing work. Trigger BEFORE declaring anything ready or presenting it as finished.
12 other projects use a version of this.
Adopted by
Most recently taken up by
- JeffreyFerreiras/ai-skillstheir own version, first seen Nov 1, 2026
- rosslevinsky/portable-agent-skillstheir own version, first seen Oct 15, 2026
- gigio1023/agent-skillstheir own version, first seen Oct 13, 2026
- gigio1023/gigio-skillstheir own version, first seen Oct 13, 2026
- raine/consult-llm-mcptheir own version, first seen Oct 8, 2026
- HACK-WU/skillstheir own version, first seen Sep 25, 2026
Other versions12 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 12
- raine/consult-llm-mcp★ 148same name
- 9thLevelSoftware/legion★ 76same name
- iamneilroberts/claude-skills★ 26same name
- rosslevinsky/portable-agent-skills★ 12same name
- gigio1023/agent-skills★ 2same name
- gigio1023/gigio-skills★ 2same name
- HACK-WU/skills★ 2same name
- kbichave/skills★ 2same name
- JeffreyFerreiras/ai-skills★ 1same name
- patmagee/skills★ 1same name
2 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 repository6 other files it gives its agents.
- extract-approachSkill
- focus-groupSkill
- sales-councilSkill
- second-brainSkill
- storm-researchSkill
- vault-gardenerSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 11 edited versions we read keep these.
1
Distinctive
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 14
No READY / done / ship verdict on self-generated work without independent panel verdicts.
“Common” is measured: kept by at least 6 in 10 of the 11 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
Review Panel
Overview
The maker never grades its own homework. The agent that produced work never decides it's ready — a panel of independent, hard-to-please reviewer subagents grades it against documented standards first. A model reviewing its own output is structurally compromised: it reuses the same reasoning that produced the work, forgives the gaps it already knows about, and mixes maker-knowledge into the verdict ("I couldn't verify X, so I left it out" is the maker lobbying, not a review). Self-reflection inside the maker plus independent graders outside it stack; neither replaces the other.
The Iron Rule
No READY / done / ship verdict on self-generated work without independent panel verdicts. Not for small artifacts, not under time pressure, not because the self-review "already found the issues."
Process
- Fix the standards first. Find the documented standards the work must meet (project docs, skill checklists, brand voice, user requirements). None written? Extract a checklist from the user's request before empaneling — reviewers grade against a checklist, not vibes.
- Empanel 2–4 reviewers with distinct lenses. Each is a fresh subagent that receives ONLY: the task brief, the artifact, the standards, and its reviewer charge. Never the maker's reasoning, self-evaluation, or "known limitations."
- Reviewer charge (include verbatim): "You are a hard-to-please reviewer. Your job is to find reasons this fails the standards, not to appreciate it. Grade each standard PASS/FAIL with evidence. Uncertain → FAIL. End with verdict: SHIP or REVISE, plus your top 3 specific objections."
- Iterate. REVISE verdicts go back to the maker with the objections; revise; re-run the failed reviewers on the new version. Max 3 rounds — then deliver to the human with unresolved objections attached. Run reviewers in the foreground and collect every verdict before proceeding — never end your turn while reviewers are still running.
- Report. Deliver the work with panel verdicts and what changed per round. Never present panel-less work as finished.
Default panels by work type
| Work | Lenses |
| Copy / emails / marketing | standards checker · target-reader skeptic (would THIS person reply?) · AI-tell hunter |
| Docs / proposals / reports | requirements-compliance checker · hostile evaluator scoring as the recipient · clarity editor |
| Plans / strategies | feasibility engineer · value skeptic (why does this matter?) · risk finder |
| Code | correctness · simplicity/maintainability · edge cases + security — or route to your code-review tooling (/review, /code-review, or a second-model reviewer) |
| Research | source verifier · missing-perspective finder (storm-research Phase 4 is self-critique — still empanel) |
Scaling: 1 reviewer minimum for small-stakes artifacts; the full panel is the default; high-stakes work adds a second-model reviewer (a different vendor's model, if you have one wired up).
Rationalization table
| Excuse | Reality |
| "I already critiqued it myself, honestly" | The baseline failure. Self-review reuses the maker's blind spots and forgives known gaps. |
| "It's small / just a draft" | Small artifacts get 1 reviewer, not zero. Anything shown to the human is a deliverable. |
| "User is waiting / time pressure" | A reviewer round takes 1–2 minutes. Shipping unvetted work costs more. |
| "The model self-validates at high effort" | Self-validation makes the maker honest inside its role; the independent grader sits outside it. Stack both. |
| "Reviewers will just agree with me" | Then the charge is too soft — a reviewer that never FAILs anything is broken; re-charge it. |
Red flags — stop and empanel
- About to type "READY", "done", "ship it", or a self-assigned quality score
- Writing a "quality evaluation" section about your own output
- Passing your own caveats or justifications along to a reviewer
- Skipping re-review after revising
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.