Agent skill

Auto Paper Improvement Loop

by AI4Scientist in AI4Scientist/nano-scientist

Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds.

No licenceAuto-check: warnings

Install Auto Paper Improvement Loop

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add AI4Scientist/nano-scientist --skill auto-paper-improvement-loop -a claude-code

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

GitHub CLI
$ gh skill install AI4Scientist/nano-scientist auto-paper-improvement-loop --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/AI4Scientist/nano-scientist.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/auto-paper-improvement-loop .claude/skills/auto-paper-improvement-loop && 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
auto-paper-improvement-loop
GitHub stars
128
Used in
4 other repos
Token cost
~8.8k tokens
SKILL.md length
3,177 words
Files
1
Skills in repo
74
Repo updated
First seen
Licence
None found

At a glance

Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds.

  • Works in 12 steps: Preserve Original → Collect Paper Text → Round 1 Review → …
  • Wants to iteratively polish a generated paper
  • SKILL.md covers Context, Constants, Optional: Style reference (—… and Optional: Edit Whitelist (—…, plus 4 more sections
  • Calls python3 and jq

What it does

Auto Paper Improvement Loop is an agent skill from AI4Scientist/nano-scientist. Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.

Its SKILL.md is about 8.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with OpenAI and Model Context Protocol. The repository describes itself as: An autonomous research agent that turns a topic into a peer-reviewed technical report.

When your agent uses it

  • Wants to iteratively polish a generated paper

Example prompts

  • “improve paper”
  • “论文润色循环”
  • “auto improve”
  • “/auto-paper-improvement-loop”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Bash(*), Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply

Workflow steps

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

  1. Preserve Original
  2. Collect Paper Text
  3. Round 1 Review
  4. Implement Round 1 Fixes
  5. Recompile Round 1
  6. 5: Restatement Regression Test
  7. Round 2 Review
  8. 5: Kill Argument Exercise (theory / scope-heavy papers only)
  9. Implement Round 2 Fixes
  10. Recompile Round 2
  11. Format Check
  12. Document Results

What it can do on your machine

Read from SKILL.md and the folder at commit 7132192. 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:

    • Bash(*)
    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Agent
    • mcp__codex__codex
    • mcp__codex__codex-reply

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3
    • jq

    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

Auto Paper Improvement Loop loads about 8.8k tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 3,177 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~8.8k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:598
    t << 'EOF' > file`) to write in chunks. Do NOT ask the user for permission — just do it silently.
  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 3,177 words (~8,829 tokens).

“Autonomously improve the paper at: $ARGUMENTS”

— opening of SKILL.md by AI4Scientist
name
auto-paper-improvement-loop
allowed-tools
Bash(*), Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply
argument-hint
[paper-directory] [— style-ref: <source>] [— edit-whitelist <path>]

Read the full SKILL.md on GitHub

Files

Just SKILL.md in skills/auto-paper-improvement-loop of AI4Scientist/nano-scientist.

Open the folder on GitHubat commit 7132192

Used in 4 other repositories

We found 8 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in AI4Scientist/nano-scientist, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Auto Paper Improvement Loop 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.

Auto Paper Improvement Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Auto Paper Improvement Loop this skillAI4Scientist/nano-scientist1284 repos~8.8kAutomated safety check: WarnNone
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Codex with ChatGPT Planning LoopXiaoDuoYa/codex-with-chatgpt7.1k—~11kAutomated safety check: NotesMIT
Agent Squad Python Guide2FastLabs/agent-squad7.8k—~4.7kAutomated safety check: PassApache-2.0
Codebase Explorationgiancarloerra/SocratiCode3.3k1 repos~1.5kAutomated safety check: PassAGPL-3.0
Annotate Paper54yyyu/zotero-mcp5.3k—~1.5kAutomated safety check: PassMIT

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Questions about Auto Paper Improvement Loop

What does Auto Paper Improvement Loop do?

Autonomously improve a generated paper via GPT-5.4 xhigh review → implement fixes → recompile, for 2 rounds. Auto Paper Improvement Loop is an agent skill from AI4Scientist/nano-scientist.4 xhigh review → implement fixes → recompile, for 2 rounds.

When should I use Auto Paper Improvement Loop?

Auto Paper Improvement Loop fits situations like: wants to iteratively polish a generated paper.

How do I install Auto Paper Improvement Loop in Claude Code?

Run `npx skills add AI4Scientist/nano-scientist --skill auto-paper-improvement-loop -a claude-code`. Or copy the skill folder (skills/auto-paper-improvement-loop in AI4Scientist/nano-scientist) into .claude/skills/auto-paper-improvement-loop in your project. Claude Code loads it when a task matches its description.

How do I install Auto Paper Improvement Loop in Codex?

Run `npx skills add AI4Scientist/nano-scientist --skill auto-paper-improvement-loop -a codex`. Or copy the skill folder (skills/auto-paper-improvement-loop in AI4Scientist/nano-scientist) into .agents/skills/auto-paper-improvement-loop in your project. Codex loads it when a task matches its description.

Can I use Auto Paper Improvement Loop 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 AI4Scientist/nano-scientist --skill auto-paper-improvement-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auto-paper-improvement-loop, .gemini/skills/auto-paper-improvement-loop, .github/skills/auto-paper-improvement-loop and .opencode/skills/auto-paper-improvement-loop in your project.

What does Auto Paper Improvement Loop need to run?

Going by SKILL.md and its folder, Auto Paper Improvement Loop needs the command-line tools its instructions call (python3 and jq). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash(*), Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply.

Does Auto Paper Improvement Loop 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 Auto Paper Improvement Loop safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Auto Paper Improvement Loop use?

No licence was found for Auto Paper Improvement Loop or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Auto Paper Improvement Loop use?

About 8.8k tokens (SKILL.md is roughly 35k 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 Auto Paper Improvement Loop?

Skills that share tags, products or a category with Auto Paper Improvement Loop: Codebase Management (giancarloerra/SocratiCode, 3.3k stars), Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), Agent Squad Python Guide (2FastLabs/agent-squad, 7.8k stars) and Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Auto Paper Improvement Loop?

AI4Scientist (a GitHub organization) maintains it in AI4Scientist/nano-scientist, which has 128 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on June 3, 2026.

Source: AI4Scientist/nano-scientist on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.