auto-paper-improvement-loop

name	auto-paper-improvement-loop
description	Autonomously improve a generated paper via external reviewer model 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.
argument-hint	["paper-directory"]
allowed-tools	Bash(*), Read, Write, Edit, Grep, Glob, Agent, mcp__codex__codex, mcp__codex__codex-reply

Auto Paper Improvement Loop: Review → Fix → Recompile

Autonomously improve the paper at: $ARGUMENTS

Context

Runs after /paper-write + /paper-compile. Iterates on writing quality (not research).

Constants

• MAX_ROUNDS = 2 — Round 1 catches structural issues, Round 2 catches presentation issues.
• REVIEWER_SCRIPT — External reviewer script. Thread via _reviewer_thread.json.
• HUMAN_CHECKPOINT = false — When true, pause after each review for user input.
• LATEX_ENGINE — Auto-detect: ctex/xelatex in main.tex → xelatex, otherwise pdflatex.
• CUSTOM_REQUIREMENTS — Highest priority.

State Persistence

Writes PAPER_IMPROVEMENT_STATE.json after each round for crash recovery:

{"current_round": 1, "last_score": 6, "status": "in_progress", "timestamp": "..."}

On startup: if exists + in_progress + <24h → resume. Otherwise start fresh.

Workflow

Step 0: Preserve Original

cp paper/main.pdf paper/main_round0_original.pdf

Step 1: Collect Paper Text

Concatenate all paper/sections/*.tex for review.

Step 2: Round 1 Review

Send the full paper text to the external reviewer via reviewer_client.py:

mkdir -p _tmp
cat << 'REVIEW_EOF' > _tmp/_review_prompt.txt
You are reviewing an academic paper. Please provide a detailed, structured review.

## Full Paper Text:
REVIEW_EOF
cat _tmp/_paper_full_text.tex >> _tmp/_review_prompt.txt
cat << 'REVIEW_EOF' >> _tmp/_review_prompt.txt

## Review Instructions
Please act as a senior reviewer. Provide:
1. **Overall Score** (1-10, where 6 = weak accept, 7 = accept)
2. **Summary** (2-3 sentences)
3. **Strengths** (3-5 bullet points)
4. **Weaknesses** (categorized as CRITICAL / MAJOR / MINOR, each with specific location and actionable fix)
   - Check for "figure-as-subject" AI pattern: paragraphs starting with "图X展示了"/"As shown in Figure X" — flag as MAJOR if ≥3 occurrences
5. **Verdict**: "Accept" / "Almost" / "Reject"
6. **Actionable Fixes** (ordered by priority, each with exact section and what to change)
REVIEW_EOF
PYTHON=$(command -v python3 2>/dev/null || command -v python 2>/dev/null)
$PYTHON "$REVIEWER_SCRIPT" --prompt-file _tmp/_review_prompt.txt --thread-file _tmp/_reviewer_thread.json 2>&1 | tee _tmp/_round1_review.txt

If the reviewer script fails (API key not configured or network error), perform the review using self-analysis — act as a senior reviewer, score honestly, and proceed to Step 3. Cross-model review is preferred for objectivity but not required.

Step 2b: Human Checkpoint (if enabled)

Present score + weaknesses. Wait for "go" / custom instructions / "skip N" / "stop". Non-interactive mode: auto-proceed.

Step 3: Implement Round 1 Fixes

Priority: CRITICAL → MAJOR → MINOR.

Common fix patterns:

Issue	Fix
Assumption-model mismatch	Rewrite assumption, add bridging proposition
Overclaims	Soften: "validate"→"demonstrate relevance"
Missing metrics	Add quantitative table with caveats
Notation confusion	Rename globally, add Notation paragraph
Figure-as-subject writing	Rewrite: move figure ref to parenthetical, lead with analysis point
Missing references	Add to bib, cite appropriately

Step 4: Recompile Round 1

Auto-detect engine. Manual 4-step: engine→bibtex→engine→engine. Save main_round1.pdf.

Step 5-6: Round 2 Review + Fixes

Same process. Use same _tmp/_reviewer_thread.json for context continuity (multi-turn dialogue is automatic):

cat << 'REVIEW_EOF' > _tmp/_review_prompt.txt
Since your last review, we have implemented the following fixes:
[list the fixes from Step 3]

Please re-review the updated paper. Focus on:
1. Were the CRITICAL/MAJOR issues adequately addressed?
2. Any new issues introduced by the fixes?
3. Updated score and verdict.

## Updated Paper Text:
REVIEW_EOF
cat _tmp/_paper_full_text.tex >> _tmp/_review_prompt.txt
PYTHON=$(command -v python3 2>/dev/null || command -v python 2>/dev/null)
$PYTHON "$REVIEWER_SCRIPT" --prompt-file _tmp/_review_prompt.txt --thread-file _tmp/_reviewer_thread.json 2>&1 | tee _tmp/_round2_review.txt

If reviewer unavailable, use self-analysis for Round 2 as well.

Step 7: Recompile Round 2

Save main_round2.pdf.

Step 8: Format Check

Check overfull hbox (>10pt → fix), page count vs limit, underfull warnings.

Step 9: Document Results

Create paper/PAPER_IMPROVEMENT_LOG.md：

# Paper Improvement Log

## Score Progression

| Round | Score | Verdict | Key Changes |
|-------|-------|---------|-------------|
| Round 0 (original) | X/10 | No/Almost/Yes | Baseline |
| Round 1 | Y/10 | No/Almost/Yes | [summary of fixes] |
| Round 2 | Z/10 | No/Almost/Yes | [summary of fixes] |

## Round 1 Review & Fixes

### Review (full text)
[Complete raw review text, verbatim]

### Fixes Implemented
1. [Fix description + which files changed]
2. [Fix description]

## Round 2 Review & Fixes

### Review (full text)
[Complete raw review text, verbatim]

### Fixes Implemented
1. [Fix description]
2. [Fix description]

## PDFs
| File | Size | Description |
|------|------|-------------|
| main_round0_original.pdf | X KB | Before improvement |
| main_round1.pdf | X KB | After round 1 |
| main_round2.pdf | X KB | After round 2 (final) |
| main.pdf | X KB | = round2 |

Output

paper/
├── main_round0_original.pdf
├── main_round1.pdf
├── main_round2.pdf (final)
├── main.pdf (= round2)
└── PAPER_IMPROVEMENT_LOG.md

Key Rules

• Preserve all PDF versions
• Save full raw review text (don't truncate)
• Same thread file for Round 2 (context continuity)
• Always recompile after fixes
• Don't fabricate experimental results
• Soften overclaims rather than adding unsupported claims
• Global consistency when renaming notation (all files)
• ⛔ Main output: paper/main.pdf + paper/PAPER_IMPROVEMENT_LOG.md. Don't write extra reports (e.g. AUTO_PAPER_IMPROVEMENT_REPORT.md, AUTO_PAPER_IMPROVEMENT_FINAL_REPORT.md) to root
• ⛔ Temp files (_review_prompt.txt, _paper_full_text.tex, _round1_review.txt etc.) go to _tmp/
• Large files: Bash heredoc