Agent skill

Paper Version

by claesbackman in claesbackman/AI-research-feedback

Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.

MITAuto-check: notesDocuments & Office

Install Paper Version

skills CLI
$ npx skills add claesbackman/AI-research-feedback --skill paper-version -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install claesbackman/AI-research-feedback paper-version --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/claesbackman/AI-research-feedback.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Skills/paper-version .claude/skills/paper-version && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
paper-version
GitHub stars
493
Token cost
~4k tokens
SKILL.md length
2,027 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.

  • Works in 6 steps: Validate input → Reader Agent → Writer Agent → …
  • Tasks that involve LaTeX
  • SKILL.md covers Input, Format definitions and Instructions
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Paper Version is an agent skill from claesbackman/AI-research-feedback. Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering LaTeX and HTML artifacts. It works with LaTeX and GitHub. The repository describes itself as: A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman. The licence is MIT.

When your agent uses it

  • Tasks that involve LaTeX
  • Tasks that involve HTML artifacts

Example prompts

  • “/paper-version”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, Bash, Agent

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Validate input
  2. Reader Agent
  3. Writer Agent
  4. Reviewer Agent
  5. Pause and present review
  6. Website Agent

What it can do on your machine

Read from SKILL.md and the folder at commit d129756. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • Bash
    • Agent

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Paper Version loads about 4k tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 2,027 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Glob, Grep, Bash, Agent

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from claesbackman/AI-research-feedback at commit d129756, republished under its MIT licence (© claesbackman). 2,027 words, ~3,970 tokens.

Download SKILL.mdSave it as .claude/skills/paper-version/SKILL.md (or your agent's skills folder).
name
paper-version
description
Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.
allowed-tools
Read, Write, Edit, Glob, Grep, Bash, Agent
user-invocable
true
argument-hint
brief|1page|5page
disable-model-invocation
true

Paper Versions

Convert a LaTeX research paper project into an accessible audience-facing version, review it for accuracy, and produce a standalone HTML page.

Input

  • $ARGUMENTS[0] — Output format: brief, 1page, or 5page (required)

Format definitions

  • brief — A structured 2-page policy brief with fixed sections: The Question, What We Do, Key Findings, Policy Implications, Caveats. Formal but accessible. No jargon.
  • 1page — One flowing page of prose for a general audience. No section headers. Written like a short article. Leads with the main finding.
  • 5page — A five-page narrative summary with light structure (Background, What We Did, What We Found, Why It Matters, Limitations). Accessible to an educated non-specialist.

Instructions

Step 0 — Validate input

If $ARGUMENTS[0] is not one of brief, 1page, 5page, stop and tell the user: "Please specify a format: brief, 1page, or 5page."

Set FORMAT = the argument value.


Step 1 — Reader Agent

Launch an Agent (subagent_type: general-purpose) with this task:

You are reading a LaTeX research paper project. Your job is to extract the full content of the paper into a clean, structured plain-text representation that will be used by a writer agent.

Instructions:

  1. Find the main .tex file in the current directory. It is usually the file that contains \documentclass or \begin{document}. Use Glob to search for **/*.tex files, then identify the root file.
  2. Read the root .tex file. Wherever you find \input{...} or \include{...} commands, read those files too, recursively, until you have assembled the full paper text.
  3. Strip LaTeX markup: remove commands like \textbf{}, \emph{}, \cite{}, \label{}, \ref{}, \footnote{}, equation environments, figure environments, table environments. Keep the text content. For tables, summarize the key numbers in prose form. For figures, note what the figure shows based on the caption.
  4. Extract and clearly label these components:
    • Title
    • Authors
    • Abstract (verbatim)
    • Introduction (full text)
    • Data/Empirical Setting (if present)
    • Methods/Approach (condensed)
    • Main Results — list every key quantitative finding, with exact numbers, units, and confidence intervals as stated in the paper. Be exhaustive here.
    • Robustness/Heterogeneity (condensed)
    • Conclusion
    • Key claims made by the authors — list every causal or interpretive claim the authors make explicitly, noting the exact language they use (e.g., "we find that X causes Y" vs. "X is associated with Y")
  5. Extract figure information: scan the full .tex source for \includegraphics commands. For each one, record:
    • The filename as specified (e.g., figures/fig1 or fig_results)
    • The caption text from the nearest \caption{} command
    • Which section of the paper the figure appears in List these under a Figures section in your output, formatted as: FIGURE: [filename] | CAPTION: [caption text] | SECTION: [section name]
  6. Identify the 1-2 figures that best illustrate the paper's main finding and mark them with [KEY FIGURE].
  7. Return the full extraction as structured markdown. Do not summarize or interpret — just extract.

Save the Reader Agent's output to output/paper_extraction.md. Create the output/ directory if it does not exist.

After the Reader Agent finishes, scan the project directory for image files that match the extracted figure filenames. Use Glob to search for **/*.png, **/*.jpg, and **/*.jpeg. For each figure listed as [KEY FIGURE] in paper_extraction.md, check whether a matching PNG or JPG file exists (try the filename with and without extension, and with common path prefixes like figures/, Figures/, fig/). Build a list of embeddable figures — those where a .png or .jpg file was found — and save it to output/figures_list.md in this format:

EMBEDDABLE: [relative path from project root] | CAPTION: [caption text]
NOT FOUND (PDF or missing): [filename] | CAPTION: [caption text]

If no PNG/JPG figures are found at all, note that in output/figures_list.md and continue — the HTML will be text-only.


Step 2 — Writer Agent

Launch an Agent (subagent_type: general-purpose) with this task, passing it the content of output/paper_extraction.md and the value of FORMAT:

You are a science writer creating an accessible version of an economics research paper for a general audience.

Paper content: [paste full content of output/paper_extraction.md]

Output format requested: [FORMAT]

Format instructions:

For brief — Write a structured policy brief. Use exactly these section headers:

  • The Question — What problem does this paper address? (2-3 sentences)
  • What We Do — How do the authors study it? Data, setting, method in plain language. (3-4 sentences)
  • Key Findings — The main quantitative results. Report actual numbers. (4-6 bullet points, each 1-2 sentences)
  • Policy Implications — What do these findings suggest for policy? Be concrete. (3-5 sentences)
  • Caveats — Limitations the authors themselves acknowledge. (2-3 sentences) Total length: approximately 500-600 words.

For 1page — Write one page of flowing prose. No section headers. Open with the main finding stated plainly. Use accessible analogies where helpful. Do not use academic hedging or jargon. End with why it matters. Total length: approximately 350-400 words.

For 5page — Write a 5-page narrative summary with these light headers:

  • Background — Context and motivation
  • What We Did — Data, setting, approach
  • What We Found — Results in detail, with numbers
  • Why It Matters — Implications
  • Limitations — What the paper cannot establish Total length: approximately 1400-1600 words.

General writing rules (all formats):

  • Write for an intelligent adult with no economics background
  • Report key numbers — do not vague them out
  • Do not overclaim causality beyond what the paper itself claims — match the paper's own language precisely
  • No passive voice where avoidable
  • No bullet points except where explicitly called for above
  • No jargon without explanation

Key findings callout: Identify the single most important quantitative finding — the one number or result a reader should walk away remembering. Write it as a short punchy sentence (max 25 words). Mark it clearly in your output with the tag [CALLOUT]: at the start of the line, e.g.: [CALLOUT]: Homeowners in the top wealth decile hold 40% of all housing wealth, despite representing only 10% of households. This will be displayed as a highlighted box on the webpage.

Return only the finished draft (including the [CALLOUT] line), with no preamble or meta-commentary.

Save the Writer Agent's output to output/[FORMAT]_draft.md (e.g., output/brief_draft.md).


Step 3 — Reviewer Agent

Launch an Agent (subagent_type: general-purpose) with this task:

You are a fact-checker and editorial reviewer. You will compare a summary/brief of an economics paper against the original paper's extracted content, and produce a structured review report.

Original paper extraction: [paste full content of output/paper_extraction.md]

Draft to review: [paste full content of output/[FORMAT]_draft.md]

Your job — check for three categories of issues:

1. Factual accuracy Go through every quantitative claim, statistic, or finding stated in the draft. For each one, verify it against the original extraction. Flag anything that:

  • Uses a wrong number
  • Changes units or direction of an effect
  • Attributes a finding to the wrong group or condition
  • Omits a critical qualifier (e.g., "only for renters" or "only in the short run")

2. Overclaiming Compare every causal or interpretive claim in the draft against the exact language in the original paper. Flag anywhere the draft uses stronger language than the paper (e.g., draft says "causes" when paper says "is associated with"; draft says "proves" when paper says "suggests").

3. Framing consistency Flag anywhere the draft:

  • Shifts the emphasis of the findings away from what the paper presents as primary
  • Buries or omits a key finding the paper treats as central
  • Introduces an implication the paper does not make

Output format: Produce a numbered list of issues found. For each issue, state:

  • Category (Factual / Overclaiming / Framing)
  • Location in draft (quote the relevant phrase)
  • The problem (what is wrong or overstated)
  • Suggested fix (what it should say instead, with reference to the source)

If no issues are found in a category, say so explicitly. End with an overall verdict: PASS (ready to use with minor edits), REVISE (needs targeted fixes before use), or MAJOR REVISION (significant accuracy or framing problems).

Save the Reviewer Agent's output to output/[FORMAT]_review.md.


Show full SKILL.md (778 more words)Show less
Step 4 — Pause and present review

After the Reviewer Agent finishes:

  1. Read output/[FORMAT]_review.md and display its full contents to the user.
  2. Tell the user: "The draft is saved at output/[FORMAT]_draft.md. Edit it as needed before proceeding. When you are ready to generate the HTML, reply proceed. To cancel, reply cancel."
  3. Wait for the user's response.
    • If the user says cancel or anything indicating they want to stop, end the skill.
    • If the user says proceed or any clear affirmation, continue to Step 5.

Step 5 — Website Agent

Read the current contents of output/[FORMAT]_draft.md (which may now be edited by the user).

Launch an Agent (subagent_type: general-purpose) with this task:

You are building a clean standalone HTML page for an economics research paper summary. This page should have no JavaScript dependencies, use a single <style> block in <head>, and be ready to deploy on GitHub Pages.

Paper title: [extracted title from paper_extraction.md] Authors: [extracted authors from paper_extraction.md] Abstract: [extracted abstract from paper_extraction.md] Format type: [FORMAT] (brief / 1page / 5page) Content: [paste full content of output/[FORMAT]_draft.md — strip the [CALLOUT]: line from the body text, it will be rendered separately as a callout box] Callout text: [the sentence that was tagged [CALLOUT]: in the draft] Embeddable figures: [paste content of output/figures_list.md — use only lines marked EMBEDDABLE]

Build the HTML page with these requirements:

<head> — Open Graph and meta tags: Include these meta tags so the page looks good when shared on social media:

html
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="[first 150 characters of the abstract]">
<meta property="og:title" content="[paper title]">
<meta property="og:description" content="[first 150 characters of the abstract]">
<meta property="og:type" content="article">
<meta property="og:article:author" content="[authors]">
<meta name="twitter:card" content="summary">
<meta name="twitter:title" content="[paper title]">
<meta name="twitter:description" content="[first 150 characters of the abstract]">

Layout and structure:

  • Single-column, centered, max-width 740px
  • Header area: paper title, authors, format badge, today's date
  • Immediately below the header: the callout box (see styling below)
  • Then the body content
  • If format is brief, render the section headers as <h2> elements
  • If format is 1page or 5page, use <h2> only for the light section headers if present
  • After the body text: any embeddable figures (see figure section below)
  • Footer: "This is a [format label]. The full paper is available <a href="#">here</a>."

Callout box: Render the callout sentence as a visually distinct block immediately after the header and before the body text:

html
<div class="callout">
  <span class="callout-label">Key Finding</span>
  <p>[callout text]</p>
</div>

Style it as: background #f0ebe2, left border 4px solid #8b7355, padding 1rem 1.25rem, margin 2rem 0. The label: display block, font-size 0.75rem, font-weight 700, text-transform uppercase, letter-spacing 0.08em, color #8b7355, margin-bottom 0.4rem. The paragraph: margin 0, font-size 1.05rem, font-style italic, color #1a1a1a.

Figures: For each embeddable figure provided, add an <figure> block after the main body text and before the footer:

html
<figure>
  <img src="[relative path from output/ — prepend ../ to the project-root-relative path]" alt="[caption text]" style="max-width:100%;height:auto;display:block;margin:0 auto;">
  <figcaption>[caption text]</figcaption>
</figure>

If the figures list says "NOT FOUND" for all figures, omit the figures section entirely. Add a <h2>Figures</h2> header above the figure block only if at least one figure is embeddable. Figure caption style: font-size 0.85rem, color #555, text-align center, margin-top 0.5rem, font-style italic.

Full CSS (in <style> block in <head>):

css
*, *::before, *::after { box-sizing: border-box; }
body { font-family: system-ui, -apple-system, Georgia, serif; background: #fafaf8; color: #1a1a1a; font-size: 18px; line-height: 1.7; margin: 0; padding: 2rem 1rem; }
.container { max-width: 740px; margin: 0 auto; }
.header { margin-bottom: 2rem; }
.title { font-size: 2rem; font-weight: 700; line-height: 1.25; margin: 0 0 0.4rem 0; }
.authors { font-size: 1rem; color: #555; margin: 0 0 0.6rem 0; }
.meta { display: flex; align-items: center; gap: 0.75rem; font-size: 0.85rem; color: #888; }
.badge { background: #e8e4dd; color: #555; font-size: 0.8rem; padding: 3px 10px; border-radius: 20px; font-weight: 500; }
.callout { background: #f0ebe2; border-left: 4px solid #8b7355; padding: 1rem 1.25rem; margin: 2rem 0; }
.callout-label { display: block; font-size: 0.75rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: #8b7355; margin-bottom: 0.4rem; }
.callout p { margin: 0; font-size: 1.05rem; font-style: italic; }
h2 { font-size: 1.15rem; font-weight: 600; color: #1a1a1a; margin-top: 2rem; border-bottom: 1px solid #ddd; padding-bottom: 4px; }
p { margin: 0 0 1rem 0; }
ul { margin: 0 0 1rem 0; padding-left: 1.2rem; }
li { margin-bottom: 0.5rem; }
figure { margin: 1.5rem 0; }
figcaption { font-size: 0.85rem; color: #555; text-align: center; margin-top: 0.5rem; font-style: italic; }
.footer { margin-top: 3rem; padding-top: 1rem; border-top: 1px solid #ddd; font-size: 0.85rem; color: #888; }
.footer a { color: #555; }
@media (max-width: 600px) { body { font-size: 16px; padding: 1rem 0.75rem; } .title { font-size: 1.5rem; } }

Return only the complete HTML file contents, nothing else.

Save the Website Agent's output to output/index.html.

Tell the user: "Done. Files produced:

  • output/[FORMAT]_draft.md — your draft
  • output/[FORMAT]_review.md — reviewer notes
  • output/index.html — standalone HTML page

To publish on GitHub Pages: commit the output/ folder and enable Pages in your repo settings, or copy index.html to a Pages repo."

© claesbackman, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Skills/paper-version of claesbackman/AI-research-feedback.

Open the folder on GitHubat commit d129756

Compare with similar skills

Paper Version next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Paper Version compared with similar skills
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Overleaf Collaboration Guidewentorai/research-plugins2981 repos~1.6kAutomated safety check: PassMIT
Research Writingalfonso0512/research-writing-skill4871 repos~818Automated safety check: PassMIT
Paper WritingMLNLP-World/Paper-Writing-Tips4.7k—~630Automated safety check: PassNone
PaperjurySpark-To-Paper-Skills/paperjury1.2k—~5.3kAutomated safety check: PassMIT

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Works with

Questions about Paper Version

What does Paper Version do?

Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages. Paper Version is an agent skill from claesbackman/AI-research-feedback. Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.

When should I use Paper Version?

Paper Version fits situations like: tasks that involve LaTeX; tasks that involve HTML artifacts.

How do I install Paper Version in Claude Code?

Run `npx skills add claesbackman/AI-research-feedback --skill paper-version -a claude-code`. Or copy the skill folder (Skills/paper-version in claesbackman/AI-research-feedback) into .claude/skills/paper-version in your project. Claude Code loads it when a task matches its description.

How do I install Paper Version in Codex?

Run `npx skills add claesbackman/AI-research-feedback --skill paper-version -a codex`. Or copy the skill folder (Skills/paper-version in claesbackman/AI-research-feedback) into .agents/skills/paper-version in your project. Codex loads it when a task matches its description.

Can I use Paper Version in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add claesbackman/AI-research-feedback --skill paper-version -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paper-version, .gemini/skills/paper-version, .github/skills/paper-version and .opencode/skills/paper-version in your project.

What does Paper Version need to run?

SKILL.md names no scripts, command-line tools or credentials: Paper Version is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, Bash, Agent.

Does Paper Version access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Paper Version safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Paper Version use?

Paper Version is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Paper Version use?

About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Paper Version?

Skills that share tags, products or a category with Paper Version: Release Latex Fork (zly2006/zhihu-plus-plus, 4.2k stars), Overleaf Collaboration Guide (wentorai/research-plugins, 298 stars), Research Writing (alfonso0512/research-writing-skill, 487 stars) and Paper Writing (MLNLP-World/Paper-Writing-Tips, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Paper Version?

claesbackman (a GitHub user) maintains it in claesbackman/AI-research-feedback, which has 493 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 25, 2026.

Source: claesbackman/AI-research-feedback on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.