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cumcm-independent-review

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

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Dépôt
Lucasuiii/modeling-workbench
Dernière activité de la source
19 septembre 2026 à 02:41
Langue détectée de SKILL.md
anglais
Étoiles
135
Forks
6

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SKILL.md
Instructions source · Aperçu en lecture seule
name
cumcm-independent-review
description
Independently review a CUMCM computation package before its claims enter validation or paper writing. Use only inside a generated independent-review package.
# 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 1. 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. 2. Reconstruct each subproblem from the supplied official files and `PROBLEM_FACTS.json`. 3. Compare the official request with the model objective, variables, constraints, assumptions, and cross-question dependencies. 4. Inspect computation entry points, run manifests, executed outputs, and result locators. 5. 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. 6. 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. 7. 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.
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