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 | $0.00019 | $0.00264 |
| Sonnet 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 11d 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.
- 11d 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 (847 stars, last pushed 17d ago), licensed MIT. It adds 39 tokens to every session and 529 once invoked, about $0.0002 per session on Opus 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.
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