# Paper Section Writer

Draft submission-ready mathematical-modeling paper sections from the approved solution...

- Repository: https://github.com/zhnnky329/MathModeling-skills (1073 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-09-24
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add zhnnky329/MathModeling-skills --skill paper-section-writer -g -a claude-code -y`
Codex: `npx skills add zhnnky329/MathModeling-skills --skill paper-section-writer -g -a codex -y`
Cursor: `npx skills add zhnnky329/MathModeling-skills --skill paper-section-writer -g -a cursor -y`
Gemini CLI: `npx skills add zhnnky329/MathModeling-skills --skill paper-section-writer -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add zhnnky329/MathModeling-skills`

## Description

Draft submission-ready mathematical-modeling paper sections from the approved solution package, frozen numbers, human decision ledger, and verified figures without searching scattered exploratory outputs or inventing interpretation.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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

The rest: https://github.com/zhnnky329/MathModeling-skills/blob/HEAD/.claude/skills/paper-section-writer/SKILL.md