referee-review
Skill20 starsChanged 22 days agoMITView on GitHub
Use when a manuscript or draft needs an independent referee-style assessment before submission, revision, or handoff. Generates a clean-room, offline (no network) referee-review report with Markdown + strict JSON output (generic profile).
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- citation-triangulationSkill
- claim-groundingSkill
- claude-cli-runnerSkill
- codex-cli-runnerSkill
- deep-literature-reviewSkill
- derivation-verifySkill
- dsh-cli-runnerSkill
- figure-hygieneSkill
- gemini-cli-runnerSkill
- hep-calcSkill
- hep-mcp-usageSkill
- idea-allocationSkill
- idea-generationSkill
- idea-pairwise-matchSkill
- idea-posteriorSkill
- julia-packageSkill
- julia-perfSkill
- kimi-cli-runnerSkill
- literature-graph-builderSkill
- literature-to-packageSkill
- markdown-hygieneSkill
- numerical-reliability-gateSkill
- opencode-cli-runnerSkill
- paper-reviserSkill
- pdg-lookupSkill
- physics-diagramsSkill
- research-harnessSkill
- research-integritySkill
- research-teamSkill
- research-writerSkill
- review-swarmSkill
- zotero-importSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 0 are distinctive, and 2 are 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.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 28
A1-A5 gate open: Run nullius integrity-record --approval-id <id> --modes <Mx,...> --notes "..." against that gate's approval_id.
- Very specific: line 55
If additional evidence is needed, populate evidence_requests with structured queries (to be executed by an external stage), and keep …
≈ “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
Referee Review (generic, offline)
This skill defines a generic (non-venue-specific) peer-review output contract that is designed to be ingested by an orchestrator as artifacts.
Output contract (must)
review.md: first line must be exactlyVERDICT: READY|NOT_READYreview.json: must validate againstschemas/review.schema.json(fail-fast)
Author pre-flight (run before submitting a packet here)
The author agent should walk the M1-M7 pre-approval ritual from
skills/research-integrity/ before posting a draft to this reviewer.
Findings the author could have caught (hallucinated citation, hallucinated
measurement, methodology-not-in-artifacts, frame-lock, etc.) should not be
the reviewer's BLOCKING items; this reviewer is for adjudication against
the packet, not for catching omissions the author skipped.
Recording the pre-flight. The M1-M7 walk is always required before posting a draft to this reviewer. How the walk is recorded depends on whether an approval gate is open:
- A1-A5 gate open. Run
nullius integrity-record --approval-id <id> --modes <Mx,...> --notes "..."against that gate'sapproval_id. The receipt is the canonical machine record of the pre-flight and is fail-closed-enforced bynullius approve(missing receipt →INTEGRITY_RECEIPT_REQUIRED, seepackages/shared/src/integrity-receipt.ts). This matches the gate-coupled "machine record" path documented inskills/research-integrity/SKILL.md§"Recording the check". - No gate open (ad-hoc draft submission). Record the M1-M7 modes
you walked inline in your response or in the notebook entry that
accompanies the draft — the narrative record from
skills/research-integrity/§"Recording the check" is the audit trail here. Do not invent a syntheticapproval_idto feed the CLI:nullius integrity-recordis parameterized onapproval_idprecisely because the receipt is the gate-coupling key, and a junk identifier pollutes.nullius/integrity_log.jsonlwithout producing any enforcement (this reviewer's pipeline does not consume the log —scripts/run_referee_review.pydoes not read it).
This reviewer remains generic and non-venue-specific; the pre-flight is the author-side discipline, not a venue requirement.
No-network / role separation
- Reviewer must not fetch new evidence (no INSPIRE/arXiv/DOI/GitHub/web).
- If additional evidence is needed, populate
evidence_requestswith structured queries (to be executed by an external stage), and keepverdict=NOT_READYwhen blocking.
CLI (deterministic, offline)
python3 scripts/run_referee_review.py --profile generic --packet fixtures/packet.md --out-dir /tmp/review_outThis writes:
/tmp/review_out/review.md/tmp/review_out/review.json
Packet format (minimal)
The packet is a Markdown file. Recommended sections:
## Paper diff## References(short bibliography or notes)## Artifact pointers(one per line, e.g.- /absolute/path/to/artifactor- file:///absolute/path/to/artifact)
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.

