code-reviewer
FreeDetect whether approved modeling code is Python or MATLAB/Beita Tianyuan and route it to the matching reviewer using the compact named-check review contract.
The English summary is being prepared. Showing the original description.
Assemble a submission-ready writer package from final method, result, robustness, figure, and human-decision artifacts, then freeze approved numerical claims with provenance.
The English summary is being prepared. Showing the original description.
See how to installReview the instructions the agent will receive before you install.
Create the writer's single source package and immutable numerical snapshot. Do not manufacture missing judgments or freeze unapproved claims.
rigor_profile is submission.qx_decisions.jsonl.results/Qx/reports/qx_solution_package_for_writer.md.modeler-decision-logger as package_signoff.results/Qx/reports/frozen_numbers.json.Each entry contains:
{
"claim_id": "q1_main_rmse",
"value": 2.4,
"unit": "units",
"source_file": "results/Q1/experiments/final/metrics/main.json",
"source_locator": "$.rmse",
"frozen_at": "ISO-8601",
"frozen_by_skill": "solution-package-builder",
"decision_id": "q1_package_signoff"
}
Use a source line only for stable text files; use a JSON path, table key, or row/column identifier for structured data.
solution-package-builder_modeler_decision.md.frozen_numbers.json before human package sign-off.When a canonical source changes after freeze:
freeze_change_log.md;No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Detect whether approved modeling code is Python or MATLAB/Beita Tianyuan and route it to the matching reviewer using the compact named-check review contract.
The English summary is being prepared. Showing the original description.
Audit whether the semantic evidence required by the active lean or submission profile exists and is current, without requiring one verbose artifact per skill or an arbitrary number of pass bullets.
The English summary is being prepared. Showing the original description.
Run scoped or final cross-media consistency checks for mathematical-modeling artifacts, comparing canonical numbers, symbols, parameters, decisions, files, and paper claims without performing full-workspace audits for low-risk changes.
The English summary is being prepared. Showing the original description.
Map contest attachments to subquestions, audit and clean raw data, and emit one reusable data profile with quality, coverage, imbalance, concentration, and method-readiness evidence for downstream risk screening.
The English summary is being prepared. Showing the original description.
Build one compact choice card at a genuine mathematical-modeling judgment point. Use before method screening, after a meaningful experiment, or before final claim/freeze approval so the human chooses the trade-off while AI handles mechanical consequences.
The English summary is being prepared. Showing the original description.
Plan the smallest set of diagnostic, comparison, paper, and appendix figures or tables needed to support verified mathematical-modeling decisions and claims.
The English summary is being prepared. Showing the original description.