agentleFS
zirui-songzirui-song/claude-skills/skills/referee-panel/SKILL.md

referee-panel

Skill17 starsChanged 3 months agoMITView on GitHub

Use before sending a design or draft to a coauthor or referee — launches five parallel adversarial subagents (identification, power, literature, data provenance, independent replication) against the research design in the repo, each citing file:line evidence, then synthesizes one threat memo ranked by probability-right × damage-if-right. Trigger phrases include "referee panel", "attack this design", "what would a referee say", "adversarial review of my paper".

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not let an agent return "the design looks sound." Its mandate is to find the failure.

    line 50
  2. Distinctive:

    Do not drop a threat because it would be expensive to address.

    line 51
  3. Very specific:

    Do not paste all five raw reports into chat — write them to results/referee/ and give the ranked memo.

    line 52

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Referee Panel

Five hostile referees in parallel, then one synthesis. Distinct from the panel-* persona skills: those channel named scholars on framing and contribution; this one attacks correctness and identification with code evidence.

Inputs (ask if not obvious)

  • Which draft / design, and which headline coefficient is the target.
  • Where the estimation code and raw data live.

The five mandates

Launch all five as parallel subagents. Each must cite file:line from the code or data — evidence, not vibes. Each is instructed to look for problems, not to balance praise.

  1. IDENTIFICATION REFEREE — bad controls, post-treatment conditioning, mechanical FE absorption, parallel-trends violations. Must end with the specific placebo or triple-diff that would falsify the claim.
  2. POWER ANALYST — for every null, run or simulate a power calculation. Is the null informative or is the design underpowered? Give an MDE in the paper's own units. (See the power-first skill for the reporting format.)
  3. LITERATURE REFEREE — find the three closest published papers and state precisely what is left after subtracting them. Be brutal about novelty.
  4. DATA PROVENANCE AUDITOR — trace every key variable back to raw source. Flag merge-key risks (gvkey/cusip zero-padding, fiscal-year alignment, survivorship) and check coverage across the sample window.
  5. INDEPENDENT REPLICATOR — re-derive the headline coefficient from raw data with its own code, without reading the existing estimation scripts. Report any discrepancy.

Synthesis

One memo. Threats ranked by P(referee is right) × damage if right. For each threat:

  • The claim it attacks, and the file:line evidence behind the attack.
  • A concrete test runnable this week.
  • The code to run it.

Flag disagreements between agents explicitly — if the replicator's coefficient differs from the identification referee's read of the spec, surface that rather than smoothing it into a consensus sentence.

Anti-patterns

  • Do not let an agent return "the design looks sound." Its mandate is to find the failure.
  • Do not drop a threat because it would be expensive to address. Rank it and let the user decide.
  • Do not paste all five raw reports into chat — write them to results/referee/ and give the ranked memo.

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.