paper

paper is a skill for Claude Code, Codex from cliffren/swf. It costs 14 tokens per session (1,945 once invoked), scanned A, original, MIT.

A writing assistant that creates an academic paper outline or drafts a named section from project documents.

In plain words
What is it for?
Use it for sections such as methods, results, introduction, discussion, abstract, supplementary material, declarations, or a submission checklist.
Why use it?
It gives research teams a structured way to turn design notes, experiments, and other project records into paper sections.

Skill for Claude CodeCodex

Part of the swf plugin — 16 skills, 1 agent shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/cliffren/swf/paper
Any agent
npx skills add cliffren/swf --skill paper
Clone the repo
git clone --depth 1 https://github.com/cliffren/swf

Made for: Claude Code, Codex.

Or install swf, the plugin that ships this one along with the rest of its 16 skills, 1 agent.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/cliffren/swf/paper.svg)](https://agentmods.dev/skills/cliffren/swf/paper)
Your own site
<a href="https://agentmods.dev/skills/cliffren/swf/paper"><img src="https://agentmods.dev/badge/skills/cliffren/swf/paper.svg" alt="Measured on agentmods" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,945 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00014 $0.01945
Opus 5 $0.00007 $0.00972
Sonnet 5 $0.00003 $0.00389
Haiku 4.5 $0.00001 $0.00194

Measured 3d ago against content hash 5c82bcfd1e7b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

paper 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 3d 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.

skills/paper/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper Writing Assistant

Generate a paper outline or draft a specific section based on project documentation.

Input

$ARGUMENTS — optional section name. If omitted, generate the full outline.

Valid section names:

Section 参数 建议写作时机 前置依赖
Methods — 核心设计 methods-core Phase 1 末期(算法确定后) design.md
Methods — 实现细节 methods-detail Phase 2 完成后 design.md + ADRs + 实验配置
Results — Benchmark results-benchmark Phase 2 完成后 benchmark 实验记录
Results — Case/Feature results-case Phase 3 完成后 case study 实验记录
Introduction intro Phase 2~3 间隙 文献调研 + outline
Discussion discussion Results 写完后 全部实验 + design 局限性
Abstract abstract 最后写 所有其他 section
Supplementary supp 和主文同步 补充图表/方法/数据
Declarations declarations Phase 6 作者/基金/数据可用性等
Checklist checklist 投稿前 检查所有必备项

Writing Order and Rationale

推荐顺序(不强制,但每一步都有理由):

1. methods-core     ← 最先写,因为算法确定就能写,不依赖实验结果
2. results-benchmark← 跑完 benchmark 趁热写,数据还在脑子里
3. results-case     ← 跑完 case study 趁热写
4. methods-detail   ← 实验做完后补充数据处理、工具版本、参数选择等细节
5. intro            ← 知道自己做出了什么,才能写好 motivation 和 contribution
6. discussion       ← 需要看完所有 results 才能讨论
7. abstract         ← 全文定型后提炼
8. supp             ← 和主文同步,最后整理

Workflow

Generate outline (/swf:paper)

  1. Read project docs:

    • docs/design.md — architecture and core methods
    • docs/adr/ — key design decisions
    • docs/experiments/ — results and findings
    • docs/experiments/collection-summary.md — if exists, use as primary results source
    • CLAUDE.md — project scope and current phase
  2. Generate outline and save to docs/paper/outline.md:

    # <Project Name>: <Tentative Paper Title>
    
    ## Abstract
    - Key points to cover: ...
    
    ## Introduction
    - Motivation: <why this problem matters>
    - Gap: <what existing methods can't do>
    - Contribution: <what we do, 2-3 bullet points>
    - Paper structure: <brief roadmap of sections>
    
    ## Methods
    ### Core Design
    - <Subsection 1 from design.md>: key concepts, core formulas
    - <Subsection 2>: ...
    ### Implementation Details
    - Data preprocessing: ...
    - Training/optimization: ...
    - Tools and versions: ...
    
    ## Results
    ### Benchmark
    - Datasets: <which ones>
    - Baselines: <which methods>
    - Metrics: <which metrics>
    - Key findings: <1-2 sentences>
    - Figures: Fig.X — <description>
    ### Case Study / Feature Validation
    - Case 1: <dataset, question, finding>
    - Case 2: ...
    - Figures: Fig.X — <description>
    ### Performance
    - Runtime, memory, scalability
    - Figure: Fig.X — <description>
    
    ## Discussion
    - Interpretation of key results
    - Comparison with related work
    - Limitations
    - Future directions
    
    ## Supplementary
    - Supplementary figures
    - Supplementary methods
    - Supplementary tables
    
    ## Declarations (投稿前必备)
    - Author contributions: <每位作者的具体贡献>
    - Competing interests: <每位作者的利益冲突声明>
    - Funding: <基金名称 + 编号>
    - Data availability: <数据存放位置、获取方式>
    - Code availability: <repo URL + license + version/commit>
    - Ethics approval: <如涉及>
    - Acknowledgments: <致谢>
    
    ## Metadata
    - Authors & affiliations
    - Corresponding author (email, ORCID)
    - Keywords (3-7)
    - Cover letter outline
    

Read the full file on GitHub · 203 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. 3d ago First seen · 203 lines · 14 tokens per session scan A 5c82bcfd1e7b

Subscribe to this mod's changes

paper is a skill published in the GitHub repository cliffren/swf (5 stars, last pushed 4mo ago), licensed MIT. It adds 14 tokens to every session and 1,945 once invoked, about $0.0001 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 2026-08-31.

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