MathModeling-skills: Skill for Claude Code

.claude/skills/paper-section-writer/SKILL.md

paper-section-writer is a skill for Claude Code from zhnnky329/MathModeling-skills. It costs 39 tokens per session (529 once invoked), scanned A, original, MIT.

A writing workflow for drafting mathematical-modeling paper sections from approved methods, fixed results, decisions, and verified figures. It avoids treating unapproved exploratory files as evidence.

In plain words
What is it for?
It helps draft method and results sections, connect claims to values and figures, describe comparisons and uncertainty, and record limitations and applicable scope.
Why use it?
It keeps the paper aligned with the final code and confirmed numbers while reducing the risk of invented explanations or unsupported claims.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is zhnnky329/MathModeling-skills's own configuration. It tells Claude Code how to work on MathModeling-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything MathModeling-skills configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/zhnnky329/MathModeling-skills/main/.claude/skills/paper-section-writer/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for paper-section-writer

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/paper-section-writer/github.svg)](https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/paper-section-writer)
Your own site
<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.

agentmods 80×15 button for paper-section-writer

Your own site · 80×15
<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>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 529 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash b26a94513d39, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

.claude/skills/paper-section-writer/SKILL.md · 76 lines

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_profile is submission.
  • 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:

  1. qx_solution_package_for_writer.md
  2. frozen_numbers.json
  3. qx_decisions.jsonl
  4. verified paper figures/tables
  5. final method explanation and robustness report for clarification

Do not hunt through raw experiment folders to invent a narrative.

Workflow

  1. Resolve the requested section and contest format.
  2. Build a claim map:
    • claim ID;
    • frozen value/source;
    • robustness support;
    • human decision ID;
    • figure/table reference;
    • limitation.
  3. Draft the method description to match the final explanation and code.
  4. Draft results with:
    • value and comparison;
    • human-confirmed physical/domain meaning;
    • uncertainty or robustness;
    • limitation and applicable scope.
  5. Mention the baseline and eliminated alternatives only when they explain a real decision.
  6. Use only Type 2–4 figures as appropriate; never place Type 1 diagnostics in the paper.
  7. Save paper/sections/qx.tex or 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.

Read the full file on GitHub · 76 lines

Changes

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.

  1. 11d ago First seen · 76 lines · 39 tokens per session scan A b26a94513d39

Subscribe to this mod's changes

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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