auto-paper-improvement-loop
Autonomously improve a generated paper via Gemini review through gemini-review MCP → 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.
npx skills add majiayu000/claude-skill-registry --skill auto-paper-improvement-loop-wanshuiyin-auto-claude-code-res --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
> Override for Codex users who want **Gemini**, not a second Codex agent, to act as the reviewer. Install this package **after** `skills/skills-codex/*`. # Auto Paper Improvement Loop: Review → Fix → Recompile Autonomously improve the paper at: **$ARGUMENTS** ## Context This skill is designed to run **after** Workflow 3 (`/paper-plan` → `/paper-figure` → `/paper-write` → `/paper-compile`). It takes a compiled paper and iteratively improves it through external LLM review. Unlike `/auto-review-loop` (which iterates on **research** — running experiments, collecting data, rewriting narrative), this skill iterates on **paper writing quality** — fixing theoretical inconsistencies, softening overclaims, adding missing content, and improving presentation. ## Constants - **MAX_ROUNDS = 2** — Two rounds of review→fix→recompile. Empirically, Round 1 catches structural issues (4→6/10), Round 2 catches remaining presentation issues (6→7/10). Diminishing returns beyond 2 rounds for writing-only improvements. - **REVIEWER_MODEL = `gemini-review`** — Gemini reviewer invoked through the local `gemini-review` MCP bridge. Set `GEMINI_REVIEW_MODEL` if you need a specific Gemini model override. - **REV
- Context
- Constants
- Inputs
- State Persistence (Compact Recovery)
- Workflow
- Step 0: Preserve Original
- Step 1: Collect Paper Text
- Step 2: Round 1 Review
- Step 2b: Human Checkpoint (if enabled)
- Step 3: Implement Round 1 Fixes
- Step 4: Recompile Round 1
- Step 5: Round 2 Review
- Step 5b: Human Checkpoint (if enabled)
- Step 6: Implement Round 2 Fixes
cp paper/main.pdf paper/main_round0_original.pdf Collect all sections in order for f in paper/sections/*.tex; do echo "% === $(basename $f) ===" cat "$f" done > /tmp/paper_full_text.txt cd paper && latexmk -C && latexmk -pdf -interaction=nonstopmode -halt-on-error main.tex cp main.pdf main_round1.pdf cp main.pdf main_round2.pdf echo "Pages: $PAGES (limit: 9 main body for ICLR/NeurIPS)"
What does the auto-paper-improvement-loop skill do?
Autonomously improve a generated paper via Gemini review through gemini-review MCP → 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 it?
Run `npx skills add majiayu000/claude-skill-registry --skill auto-paper-improvement-loop-wanshuiyin-auto-claude-code-res --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
