CUMCM Independent Review
SkillDev toolsIndependently review a CUMCM computation package before its claims enter validation or paper writing. Use only inside a generated independent-review package.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the CUMCM Independent Review skill
What this skill tells your AI
The instructions your AI receives, as published by lucasuiii/cumcm-workflow in .agents/skills/cumcm-workflow/assets/independent-review/SKILL.md and read by ahel’s 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.mdandmaterials/problem/SOURCE_MANIFEST.json. In targeted mode, also read package-rootTARGETED_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.jsonfirst. 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.
Signals
- GitHub stars
- 76
- Forks
- 5
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
cumcm-independent-review- Source
- github.com/lucasuiii/cumcm-workflow