auto-paper-improvement-loop

auto-paper-improvement-loop is an open-source data skill for Claude Code and compatible agents, published by wanshuiyin. Its author describes it as: “Autonomously improve a generated paper via GPT-5.6-Sol 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 ge…”. The project has 15k stars on GitHub and is available under the MIT license. Add it to your setup with `git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-paper-improvement-loop`.

What auto-paper-improvement-loop does

> 🔒 **Do not wrap this skill in `/loop`, `/schedule`, or `CronCreate`.** It > already loops internally (review → fix → recompile) with its own round > structure and a deliberate fresh-reviewer bias guard each round (no > `codex-reply`). Re-asking it to "improve the paper" on a > wall-clock timer produces no new signal — quality changes when the *review* > changes, not when the clock ticks — and a timed re-run that also accepts its > own output to decide when to stop crosses into self-acquittal > (`acceptance-gate.md`). Schedule the *external wait that precedes it*, not the > improvement loop.…

Installation

Add auto-paper-improvement-loop to your agent with:

git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-paper-improvement-loop

Always review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.

What's inside

The SKILL.md for auto-paper-improvement-loop is organised into these sections:

• Context
• Constants
• Optional: Style reference (— style-ref: <source>, opt-in)
• Optional: Edit Whitelist (— edit-whitelist <path>, opt-in)
• Schema
• Resolution rules
• Glob semantics
• Forbidden-operation detectors
• Behavior at loop start (before Round 1 fix-implementation)
• Behavior during fix-implementation (Steps 3 and 6)
• End-of-round surfacing
• Example invocations

When to use it

Reach for auto-paper-improvement-loop when you want data help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.

Strengths

• Clear MIT license — safe to read and adapt
• Ships in wanshuiyin/Auto-claude-code-research-in-sleep, an established project with 14,858 GitHub stars
• Actively maintained (recent commits)

Topics

Frequently asked questions

What does auto-paper-improvement-loop do?

Autonomously improve a generated paper via GPT-5.6-Sol 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.

How do I install auto-paper-improvement-loop?

Run git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-paper-improvement-loop in your agent, then reload your skills. Review the source at https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep before installing.

Is auto-paper-improvement-loop free to use?

Yes. auto-paper-improvement-loop is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.

Where does auto-paper-improvement-loop come from?

auto-paper-improvement-loop ships inside wanshuiyin/Auto-claude-code-research-in-sleep, a repository that contains 41 catalogued skills in total. The repository's 14,858 GitHub stars apply to that whole collection, not to this skill on its own.