MathModeling-skills is a collection of Claude Code and Codex skills for mathematical modeling competitions, guiding users through data analysis, method-specific checks, reproducible computations, figures, and paper audits without taking over modeling decisions. It is for contestants who want AI to handle mechanical checks while they retain responsibility for choosing methods and interpreting results. The catalogue entries form the project's skills, instructions, hook, setting, and plugin workflow.
Borrowing it
Nothing to install: this file belongs to zhnnky329/MathModeling-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhnnky329/MathModeling-skills/main/.claude/skills/python-code-reviewer/SKILL.mdgit clone --depth 1 https://github.com/zhnnky329/MathModeling-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/python-code-reviewer)<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/python-code-reviewer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/python-code-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/python-code-reviewer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/python-code-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.00637 |
| Opus 5.5 | $0.00016 | $0.00255 |
| Sonnet 5.5 | $0.00008 | $0.00127 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
python-code-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preconditions
- Python code and
code/Qx/qx_code_plan.mdexist. - Approved method decision, method card, data profile, and relevant run summary are available.
- Required inputs are accessible.
Workflow
- Resolve the approved main and usable baseline. Flag scripts for unapproved candidates unless a fallback activation exists.
- Inspect and run the code in the intended order.
- Evaluate required checks:
syntax: imports, execution, exceptions, and obvious runtime faults.input_contract: paths, fields, units, shapes, missing-data handling, and raw-data protection.method_alignment: formulas, objectives, constraints, assumptions, main/baseline roles, and fallback scope match the approved plan.reproducibility: seed, deterministic setup, dependency/runtime record, and rerun consistency.output_contract: saved tables/metrics/figures, valid run summary, comparable main/baseline metrics, degeneracy evidence, and fallback-trigger state.
- Add risk-specific checks only when relevant, such as leakage, constraint feasibility, numerical stability, or scale.
- If asked to fix findings, make minimal changes, rerun affected checks, and record the repair. Otherwise report findings without changing code.
- Save
code/Qx/reviews/qx_python_review.json.
Review Schema
{
"schema_version": 1,
"question_id": "Q1",
"language": "python",
"reviewed_files": [],
"decision_id": "q1_method_choice",
"checks": {
"syntax": {"status": "PASS", "evidence": []},
"input_contract": {"status": "PASS", "evidence": []},
"method_alignment": {"status": "PASS", "evidence": []},
"reproducibility": {"status": "PASS", "evidence": []},
"output_contract": {"status": "PASS", "evidence": []}
},
"findings": [],
"verdict": "PASSED",
"reviewed_at": "ISO-8601"
}
Statuses are PASS, FAIL, or NOT_APPLICABLE with a reason. Any required FAIL blocks G3.
Rules
- Do not pad evidence to reach a count.
- Do not fabricate execution or outputs.
- Do not approve a toy diagnostic reference as the official baseline.
- Do not silently change mathematical meaning.
- Do not create success logs beyond the review JSON.
- Treat code newer than its review as requiring the affected checks to rerun, not necessarily the entire pipeline.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 65 lines · 41 tokens per session scan A 5927bebd330b
python-code-reviewer is a skill published in the GitHub repository zhnnky329/MathModeling-skills (1,080 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 637 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
python-code-reviewer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| python-code-reviewerzhnnky329/MathModeling-skills | Skill | 1.1k | 1mo ago | MIT | A | 41 | Claude Code |
| mcore-linting-and-formattingNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 44 | Claude Code |
| python-review-checklistawslabs/cli-agent-orchestrator | Skill | 1.5k | yesterday | Apache-2.0 | A | 20 | Claude Code, Codex |
| splitting-oversized-modulesPostHog/posthog-foss | Skill | 728 | yesterday | MIT | A | 197 | Claude Code, Codex |
| splitting-oversized-modulesPostHog/posthog | Skill | 41k | yesterday | none | A | 197 | Claude Code, Codex |
| best-practicesFradSer/dotclaude | Skill | 596 | 2d ago | MIT | A | 52 | Claude Code |
| plankton-code-qualityloulanyue/awesome-claude-notes | Skill | 271 | 1mo ago | MIT | A | 34 | Claude Code |