/paper-writing-section
Write a specific section of an academic paper (Abstract, Introduction, Background, Related Work, Methods, Experiments, Results, Discussion/Conclusion) with section-specific guidance and two-pass refinement. Use when the user wants to write, draft, or improve a paper section.
$ npx -y skills add lingzhi227/agent-research-skills --skill paper-writing-section --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/paper-writing-section
Context preview
The summary Claude sees to decide when to auto-load this skill.
Write a specific section of an academic paper (Abstract, Introduction, Background, Related Work, Methods, Experiments, Results, Discussion/Conclusion) with section-specific guidance and two-pass refinement. Use when the user wants to write, draft, or improve a paper section.
SKILL.md
paper-writing-section.SKILL.mdname: paper-writing-section
description: Write a specific section of an academic paper (Abstract, Introduction, Background, Related Work, Methods, Experiments, Results, Discussion/Conclusion) with section-specific guidance and two-pass refinement. Use when the user wants to write, draft, or improve a paper section.
argument-hint: [section-name]
Paper Section Writer
Write a publication-quality section for an academic paper.
Input
- `$0` — Section name: `abstract`, `introduction`, `background`, `related-work`, `methods`, `experimental-setup`, `results`, `discussion`, `conclusion`
- `$1` — (Optional) Path to context file (research plan, results, prior sections)
Workflow
Step 1: Gather Context
Read the paper's existing `.tex` files, experiment logs, result files, and any provided context. Understand: title, contributions, methodology, key results, figures, tables.
Step 2: Write the Section
Load section-specific tips from `references/section-tips.md`. Before every paragraph, include a brief plan as a LaTeX comment (`% Plan: ...`).
Step 3: Two-Pass Refinement
Apply both refinement passes from `references/refinement-prompts.md`:
- **Pass 1**: Fix errors (unenclosed math, broken refs, hallucinated numbers, duplicate labels)
- **Pass 2**: Remove redundancies, compress, ensure smooth transitions
References
- Section writing tips: `~/.claude/skills/paper-writing-section/references/section-tips.md`
- Refinement prompts and error checklist: `~/.claude/skills/paper-writing-section/references/refinement-prompts.md`
Output
LaTeX fragment (no `\documentclass`, no preamble). All math enclosed in `$...$` or `\begin{equation}`, all figures referenced with `\ref{}`, all cited works use `\cite{}`, no placeholder text.
Quality Checklist
- All math enclosed properly
- All `\ref{}` and `\cite{}` valid
- No TODO/TBD/FIXME markers
- Numbers match experimental logs exactly
- Writing style is objective — no hype words
- Section length appropriate for venue
Related Skills
- Upstream: [data-analysis](../data-analysis/), [figure-generation](../figure-generation/), [table-generation](../table-generation/), [related-work-writing](../related-work-writing/)
- Downstream: [latex-formatting](../latex-formatting/), [citation-management](../citation-management/)
- See also: [paper-assembly](../paper-assembly/)
Read more
name: paper-writing-section description: Write a specific section of an academic paper (Abstract, Introduction, Background, Related Work, Methods, Experiments, Results, Discussion/Conclusion) with section-specific guidance and two-pass refinement. Use when the user wants to write, draft, or improve a paper section. argument-hint: [section-name]
Paper Section Writer
Write a publication-quality section for an academic paper.
Input
- `$0` — Section name: `abstract`, `introduction`, `background`, `related-work`, `methods`, `experimental-setup`, `results`, `discussion`, `conclusion`
- `$1` — (Optional) Path to context file (research plan, results, prior sections)
Workflow
Step 1: Gather Context
Read the paper's existing `.tex` files, experiment logs, result files, and any provided context. Understand: title, contributions, methodology, key results, figures, tables.
Step 2: Write the Section
Load section-specific tips from `references/section-tips.md`. Before every paragraph, include a brief plan as a LaTeX comment (`% Plan: ...`).
Step 3: Two-Pass Refinement
Apply both refinement passes from `references/refinement-prompts.md`:
- **Pass 1**: Fix errors (unenclosed math, broken refs, hallucinated numbers, duplicate labels)
- **Pass 2**: Remove redundancies, compress, ensure smooth transitions
References
- Section writing tips: `~/.claude/skills/paper-writing-section/references/section-tips.md`
- Refinement prompts and error checklist: `~/.claude/skills/paper-writing-section/references/refinement-prompts.md`
Output
LaTeX fragment (no `\documentclass`, no preamble). All math enclosed in `$...$` or `\begin{equation}`, all figures referenced with `\ref{}`, all cited works use `\cite{}`, no placeholder text.
Quality Checklist
- All math enclosed properly
- All `\ref{}` and `\cite{}` valid
- No TODO/TBD/FIXME markers
- Numbers match experimental logs exactly
- Writing style is objective — no hype words
- Section length appropriate for venue
Related Skills
- Upstream: [data-analysis](../data-analysis/), [figure-generation](../figure-generation/), [table-generation](../table-generation/), [related-work-writing](../related-work-writing/)
- Downstream: [latex-formatting](../latex-formatting/), [citation-management](../citation-management/)
- See also: [paper-assembly](../paper-assembly/)
31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.
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