| name | paper-writing |
| description | Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow. |
| argument-hint | ["narrative-report-path-or-topic"] |
| allowed-tools | Bash(*), Read, Write, Edit, Grep, Glob, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply |
Workflow 3: Paper Writing Pipeline
Orchestrate a complete paper writing workflow for: $ARGUMENTS
Overview
This skill chains five sub-skills into a single automated pipeline:
/paper-plan → /paper-figure → /paper-write → /paper-compile → /auto-paper-improvement-loop
(outline) (plots) (LaTeX) (build PDF) (review & polish ×2)
Each phase builds on the previous one's output. The final deliverable is a polished, reviewed paper/ directory with LaTeX source and compiled PDF.
Constants
- VENUE =
ICLR — Target venue. Options: ICLR, NeurIPS, ICML. Affects style file, page limit, citation format.
- MAX_IMPROVEMENT_ROUNDS = 2 — Number of review→fix→recompile rounds in the improvement loop.
- REVIEWER_MODEL =
gpt-5.4 — Model used via Codex MCP for plan review, figure review, writing review, and improvement loop.
- AUTO_PROCEED = true — Auto-continue between phases. Set
false to pause and wait for user approval after each phase.
Override inline: /paper-writing "NARRATIVE_REPORT.md" — venue: NeurIPS, wait for my approval at each step
Inputs
This pipeline accepts one of:
NARRATIVE_REPORT.md (best) — structured research narrative with claims, experiments, results, figures- Research direction + experiment results — the skill will help draft the narrative first
- Existing
PAPER_PLAN.md — skip Phase 1, start from Phase 2
The more detailed the input (especially figure descriptions and quantitative results), the better the output.
Pipeline
Phase 1: Paper Plan
Invoke /paper-plan to create the structural outline:
/paper-plan "$ARGUMENTS"
What this does:
- Parse NARRATIVE_REPORT.md for claims, evidence, and figure descriptions
- Build a Claims-Evidence Matrix — every claim maps to evidence, every experiment supports a claim
- Design section structure (5-8 sections depending on paper type)
- Plan figure/table placement with data sources
- Scaffold citation structure
- GPT-5.4 reviews the plan for completeness
Output: PAPER_PLAN.md with section plan, figure plan, citation scaffolding.
Checkpoint: Present the plan summary to the user.
📐 Paper plan complete:
- Title: [proposed title]
- Sections: [N] ([list])
- Figures: [N] auto-generated + [M] manual
- Target: [VENUE], [PAGE_LIMIT] pages
Shall I proceed with figure generation?
- User approves (or AUTO_PROCEED=true) → proceed to Phase 2.
- User requests changes → adjust plan and re-present.
Phase 2: Figure Generation
Invoke /paper-figure to generate data-driven plots and tables:
/paper-figure "PAPER_PLAN.md"
What this does:
- Read figure plan from PAPER_PLAN.md
- Generate matplotlib/seaborn plots from JSON/CSV data
- Generate LaTeX comparison tables
- Create
figures/latex_includes.tex for easy insertion
- GPT-5.4 reviews figure quality and captions
Output: figures/ directory with PDFs, generation scripts, and LaTeX snippets.
Scope: Auto-generates ~60% of figures (data plots, comparison tables). Architecture diagrams, pipeline figures, and qualitative result grids must be created manually and placed in figures/ before proceeding. See /paper-figure SKILL.md for details.
Checkpoint: List generated vs manual figures.
📊 Figures complete:
- Auto-generated: [list]
- Manual (need your input): [list]
- LaTeX snippets: figures/latex_includes.tex
[If manual figures needed]: Please add them to figures/ before I proceed.
[If all auto]: Shall I proceed with LaTeX writing?
Phase 3: LaTeX Writing
Invoke /paper-write to generate section-by-section LaTeX:
/paper-write "PAPER_PLAN.md"
What this does:
- Write each section following the plan, with proper LaTeX formatting
- Insert figure/table references from
figures/latex_includes.tex
- Build
references.bib from citation scaffolding
- Clean stale files from previous section structures
- Automated bib cleaning (remove uncited entries)
- De-AI polish (remove "delve", "pivotal", "landscape"...)
- GPT-5.4 reviews each section for quality
Output: paper/ directory with main.tex, sections/*.tex, references.bib, math_commands.tex.
Checkpoint: Report section completion.
✍️ LaTeX writing complete:
- Sections: [N] written ([list])
- Citations: [N] unique keys in references.bib
- Stale files cleaned: [list, if any]
Shall I proceed with compilation?
Phase 4: Compilation
Invoke /paper-compile to build the PDF:
/paper-compile "paper/"
What this does:
latexmk -pdf with automatic multi-pass compilation- Auto-fix common errors (missing packages, undefined refs, BibTeX syntax)
- Up to 3 compilation attempts
- Post-compilation checks: undefined refs, page count, font embedding
- Precise page verification via
pdftotext
- Stale file detection
Output: paper/main.pdf
Checkpoint: Report compilation results.
🔨 Compilation complete:
- Status: SUCCESS
- Pages: [X] (main body) + [Y] (references) + [Z] (appendix)
- Within page limit: YES/NO
- Undefined references: 0
- Undefined citations: 0
Shall I proceed with the improvement loop?
Phase 5: Auto Improvement Loop
Invoke /auto-paper-improvement-loop to polish the paper:
/auto-paper-improvement-loop "paper/"
What this does (2 rounds):
Round 1: GPT-5.4 xhigh reviews the full paper → identifies CRITICAL/MAJOR/MINOR issues → Claude Code implements fixes → recompile → save main_round1.pdf
Round 2: GPT-5.4 xhigh re-reviews with conversation context → identifies remaining issues → Claude Code implements fixes → recompile → save main_round2.pdf
Typical improvements:
- Fix assumption-model mismatches
- Soften overclaims to match evidence
- Add missing interpretations and notation
- Strengthen limitations section
- Add theory-aligned experiments if needed
Output: Three PDFs for comparison + PAPER_IMPROVEMENT_LOG.md.
Format check (included in improvement loop Step 8): After final recompilation, auto-detect and fix overfull hboxes (content exceeding margins), verify page count vs venue limit, and ensure compact formatting. Any overfull > 10pt is fixed before generating the final PDF.
Phase 6: Final Report
# Paper Writing Pipeline Report
**Input**: [NARRATIVE_REPORT.md or topic]
**Venue**: [ICLR/NeurIPS/ICML]
**Date**: [today]
## Pipeline Summary
| Phase | Status | Output |
|-------|--------|--------|
| 1. Paper Plan | ✅ | PAPER_PLAN.md |
| 2. Figures | ✅ | figures/ ([N] auto + [M] manual) |
| 3. LaTeX Writing | ✅ | paper/sections/*.tex ([N] sections, [M] citations) |
| 4. Compilation | ✅ | paper/main.pdf ([X] pages) |
| 5. Improvement | ✅ | [score0]/10 → [score2]/10 |
## Improvement Scores
| Round | Score | Key Changes |
|-------|-------|-------------|
| Round 0 | X/10 | Baseline |
| Round 1 | Y/10 | [summary] |
| Round 2 | Z/10 | [summary] |
## Deliverables
- paper/main.pdf — Final polished paper
- paper/main_round0_original.pdf — Before improvement
- paper/main_round1.pdf — After round 1
- paper/main_round2.pdf — After round 2
- paper/PAPER_IMPROVEMENT_LOG.md — Full review log
## Remaining Issues (if any)
- [items from final review that weren't addressed]
## Next Steps
- [ ] Visual inspection of PDF
- [ ] Add any missing manual figures
- [ ] Submit to [venue] via OpenReview / CMT / HotCRP
Key Rules
- Don't skip phases. Each phase builds on the previous one — skipping leads to errors.
- Checkpoint between phases when AUTO_PROCEED=false. Present results and wait for approval.
- Manual figures first. If the paper needs architecture diagrams or qualitative results, the user must provide them before Phase 3.
- Compilation must succeed before entering the improvement loop. Fix all errors first.
- Preserve all PDFs. The user needs round0/round1/round2 for comparison.
- Document everything. The pipeline report should be self-contained.
- Respect page limits. If the paper exceeds the venue limit, suggest specific cuts before the improvement loop.
Composing with Other Workflows
/idea-discovery "direction" ← Workflow 1: find ideas
implement ← write code
/run-experiment ← deploy experiments
/auto-review-loop "paper topic" ← Workflow 2: iterate research
/paper-writing "NARRATIVE_REPORT.md" ← Workflow 3: you are here
submit! 🎉
Or use /research-pipeline for the Workflow 1+2 end-to-end flow,
then /paper-writing for the final writing step.
Typical Timeline
| Phase | Duration | Can sleep? |
|---|
| 1. Paper Plan | 5-10 min | No |
| 2. Figures | 5-15 min | No |
| 3. LaTeX Writing | 15-30 min | Yes ✅ |
| 4. Compilation | 2-5 min | No |
| 5. Improvement | 15-30 min | Yes ✅ |
Total: ~45-90 min for a full paper from narrative report to polished PDF.
