一键导入
code-reviewer
Detect the language of generated modeling code and route review work to the Python or MATLAB reviewer without producing a separate saved artifact.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Detect the language of generated modeling code and route review work to the Python or MATLAB reviewer without producing a separate saved artifact.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
At a judgment point, emit the 2-3 questions only the human modeler can answer — framed as trade-offs, not answers — and refuse to answer them. The inverse of "AI answers, human confirms": here the AI asks, the human answers, then the AI assists with the consequences.
Manage the full mathematical modeling contest workflow and decide which skill should be used next.
Verify every skill that claims "completed" produced a substantive audit/review artifact on disk with ≥ 5 explicit pass items. Runs as part of the independent audit layer that does not trust any single skill's self-declaration of done.
Plan figures and tables that support the modeling logic, results, and paper narrative.
Generate publication-quality mathematical modeling figures with matplotlib, covering evaluation charts, prediction plots, optimization diagrams, mechanism schematics, heatmaps, and multi-panel layouts. Use when creating or revising figures for contest papers.
Extract, organize, and document unified model assumptions from the problem parse and candidate method pools, distinguishing necessary from simplifying assumptions.
| name | code-reviewer |
| description | Detect the language of generated modeling code and route review work to the Python or MATLAB reviewer without producing a separate saved artifact. |
| license | MIT |
Route existing modeling code to the correct language-specific reviewer.
This skill does not do deep Python or MATLAB review itself. It only checks implementation.target, inspects script extensions and code folders (code/Qx/ for Python, code/matlab/Qx/ for MATLAB), and decides whether review should be handled by python-code-reviewer or matlab-code-reviewer.
It also verifies that generated code follows the expected experiments/roundN/ output conventions before routing.
Use this skill:
python-model-code-generator or matlab-model-code-generator has produced code.result-report-generator and robustness-checker.The following should already exist or be provided:
implementation.target specified.code/Qx/ (Python) or code/matlab/Qx/ (MATLAB).code/model-code-analyzer.md.results/Qx/experiments/roundN/.Use or request:
methods/Qx/qx_method_candidates.md — candidate method pool.code/model-code-analyzer.md — code thinking document.code/Qx/ (Python .py files).code/matlab/Qx/ (MATLAB .m files).README.md in each code folder.Read implementation.target from the code thinking document or candidate pool.
python or matlab.Inspect the available code files.
code/Qx/ for .py files → route to python-code-reviewer.code/matlab/Qx/ for .m files → route to matlab-code-reviewer.Verify output structure conventions.
results/Qx/experiments/roundN/tables/, figures/, metrics/, logs/.run_summary.json generation is implemented.Check for target conflicts.
implementation.target.Hand off to the correct reviewer.
workspace/.This router does not create a persisted output artifact under workspace/.
Its only job is to choose the next reviewer and pass relevant context.
Before routing, verify at least:
code/Qx/ for Python, code/matlab/Qx/ for MATLAB).README.md with run instructions.q1_m1_baseline.py maps to M1).results/Qx/experiments/roundN/ (not old workspace/results/ paths).If any of these checks fail, pass the findings to the language-specific reviewer as pre-identified issues.
implementation.target.experiments/roundN/ structure before routing.Route to:
python-code-reviewer for Python code under code/Qx/matlab-code-reviewer for MATLAB / 北太天元 compatible code under code/matlab/Qx/The handoff should include:
README.md paths.experiments/roundN/ output structure.