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/paper-section-writer/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/paper-section-writer)<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/paper-section-writer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/paper-section-writer/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/paper-section-writer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/paper-section-writer.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 | $0.00039 | $0.00529 |
| Opus 5.5 | $0.00016 | $0.00212 |
| Sonnet 5.5 | $0.00008 | $0.00106 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
paper-section-writer 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preconditions
rigor_profileissubmission.- Final method explanation exists.
- Final result analysis exists.
- Solution package and current frozen numbers exist.
- Required human claim-scope and physical/domain-meaning decisions are recorded.
If any prerequisite is missing, return to its producer rather than drafting around the gap.
Primary Sources
Use, in order:
qx_solution_package_for_writer.mdfrozen_numbers.jsonqx_decisions.jsonl- verified paper figures/tables
- final method explanation and robustness report for clarification
Do not hunt through raw experiment folders to invent a narrative.
Workflow
- Resolve the requested section and contest format.
- Build a claim map:
- claim ID;
- frozen value/source;
- robustness support;
- human decision ID;
- figure/table reference;
- limitation.
- Draft the method description to match the final explanation and code.
- Draft results with:
- value and comparison;
- human-confirmed physical/domain meaning;
- uncertainty or robustness;
- limitation and applicable scope.
- Mention the baseline and eliminated alternatives only when they explain a real decision.
- Use only Type 2–4 figures as appropriate; never place Type 1 diagnostics in the paper.
- Save
paper/sections/qx.texor the requested Markdown section.
Human-Owned Content
The AI must not originate:
- why the method was chosen;
- what the headline number means physically;
- confidence and claim scope;
- contribution framing.
Transcribe these from the decision ledger with provenance. If absent, invoke a compact choice card and stop the final draft until answered; do not fill the paper with repeated sentinels.
Rules
- Every numerical claim must match
frozen_numbers.json. - Do not overclaim against untested methods or populations.
- Do not fabricate citations or causal meaning.
- Avoid procedural diary prose and ceremonial detail.
- Keep formulas, symbols, units, captions, and filenames consistent.
- Do not create a new decision artifact.
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 · 76 lines · 39 tokens per session scan A b26a94513d39
paper-section-writer is a skill published in the GitHub repository zhnnky329/MathModeling-skills (1,080 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 529 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.
paper-section-writer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| paper-section-writerzhnnky329/MathModeling-skills | Skill | 1.1k | 1mo ago | MIT | A | 39 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |