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Cumcm Independent Review Agent Skill

Independently review a CUMCM computation package before its claims enter validation or paper writing. Use only inside a generated independent-review package.

2k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
103
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Lucasuiii/modeling-workbench --skill cumcm-independent-review

What comes with it

4 183 bytes besides the instruction
REVIEW_REQUEST.md

The instruction itself

4 sections, as written by the author

CUMCM Independent Review

Review this freshness-bound package without consulting the originating conversation. Treat conclusions as untrusted and reconstruct only what is needed from official inputs, contracts, selected source, official runs, and outputs.

Boundaries

  • Work read-only inside the package.
  • Do not search for missing official materials. Report them as missing.
  • Do not edit, rerun, or replace the preserved execution unless the user separately authorizes a reproduction run.
  • File existence and successful execution do not prove that the model answers the official question.
  • Verify the package/upstream bindings before substantive review; a stale package is inconclusive.
  • Give exact file, formula, code, or numerical locations for every P0/P1 finding.
  • Preserve negative and inconclusive findings verbatim.

Review order

  • Read REVIEW_REQUEST.md and materials/problem/SOURCE_MANIFEST.json. In targeted mode, also read package-root TARGETED_FINDINGS.json; it is the self-contained prior-P0 brief, so do not request the complete prior review.
  • Reconstruct each subproblem from the supplied official files and PROBLEM_FACTS.json.
  • Compare the official request with the model objective, variables, constraints, assumptions, and cross-question dependencies.
  • Inspect computation entry points, run manifests, executed outputs, and result locators.
  • Challenge relevant failure classes:
  • task or target misunderstood;
  • upper/lower bound or optimization direction reversed;
  • a quantity counted twice;
  • unsupported extrapolation;
  • an observed variable omitted without justification;
  • cross-question contradiction;
  • code and mathematical formulation disagree;
  • numerical output violates units, bounds, conservation, or official constraints.
  • For targeted mode, resolve every entry in TARGETED_FINDINGS.json first. Do not repeat a full review unless the target change has global impact or current evidence reveals a new, well-supported P0.
  • Write the raw review and structured result using the supplied template.

Verdict

  • accepted: no open P0 and no material unresolved concern in scope.
  • accepted_with_concerns: no open P0; one or more P1 concerns remain.
  • revision_required: at least one open P0 requires returning to the earliest affected stage.
  • inconclusive: required material is missing or the available evidence cannot support a decision.

Classify findings as P0/P1/P2 and open/resolved/accepted_concern. State the reviewer, model if applicable, originating/reviewer task references, and independence grade. Never describe same-context review as independent; a same-model fresh task remains correlated.

How to use it

Copy the folder

Take lucasuiii/cumcm-independent-review from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.