Paper Writing

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.

In this hybrid pack, the pipeline itself is unchanged, but paper-plan and paper-write use Orchestra-adapted shared references for stronger story framing and prose guidance.

Constants

• VENUE = ICLR — Target venue. Options: ICLR, NeurIPS, ICML, CVPR, ACL, AAAI, ACM, IEEE_JOURNAL (IEEE Transactions / Letters), IEEE_CONF (IEEE conferences). Affects style file, page limit, citation format.
• MAXIMPROVEMENTROUNDS = 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.
• HUMAN_CHECKPOINT = false — When true, the improvement loop (Phase 5) pauses after each round's review to let you see the score and provide custom modification instructions. When false (default), the loop runs fully autonomously. Passed through to /auto-paper-improvement-loop.
• ILLUSTRATION = figurespec — Architecture/illustration generator for Phase 2b: figurespec (default, deterministic JSON→SVG via /figure-spec, best for architecture/workflow/topology), gemini (AI-generated via /paper-illustration, best for qualitative method illustrations; needs GEMINI_API_KEY), codex-image2 (AI-generated via /paper-illustration-image2 through the local Codex native image bridge — no external API key, uses your ChatGPT Plus/Pro quota; experimental), mermaid (Mermaid syntax via /mermaid-diagram, free, best for flowcharts), or false (skip Phase 2b, manual only).

> Override inline: /paper-writing "NARRATIVE_REPORT.md" — venue: NeurIPS, illustration: gemini, human checkpoint: true > IEEE example: /paper-writing "NARRATIVE_REPORT.md" — venue: IEEE_JOURNAL

Inputs

This pipeline accepts one of:

1. NARRATIVE_REPORT.md (best) — structured research narrative with claims, experiments, results, figures
2. Research direction + experiment results — the skill will help draft the narrative first
3. 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.

Optional: Style reference (— style-ref: , opt-in)

Lets the user steer structural style (section ordering, theorem density, sentence cadence, figure density, bibliography style) of the generated paper toward a reference paper they admire. Default OFF — when the user does not pass — style-ref, do nothing differently from before.

When — style-ref: is in $ARGUMENTS, run the helper FIRST, before Phase 1 (paper-plan):

if [ ! -f tools/extract_paper_style.py ]; then
  echo "error: tools/extract_paper_style.py not found — re-run 'bash tools/install_aris.sh' to refresh the '.aris/tools' symlink (added in #174), or copy the helper manually from the ARIS repo" >&2
  exit 1
fi
CACHE=$(python3 tools/extract_paper_style.py --source "")
case $? in
  0) ;;                                       # share $CACHE/style_profile.md with downstream WRITER phases only
  2) echo "warning: style-ref skipped (missing optional dep)" >&2 ;;
  3) echo "error: --style-ref source failed; aborting pipeline" >&2 ; exit 1 ;;
  *) echo "error: helper failed unexpectedly; aborting pipeline" >&2 ; exit 1 ;;
esac

Then forward — style-ref: only to the writer-side sub-skills:

• /paper-plan (Phase 1) — outline structure
• /paper-write (Phase 3) — section-by-section prose
• /paper-illustration (Phase 2b) — figure structural matching, optional

Sources accepted: local TeX dir / file, local PDF, arXiv id, http(s) URL. Overleaf URLs/IDs are rejected — clone via /overleaf-sync setup first and pass the local clone path.

Strict rules (full contract in tools/extract_paper_style.py docstring):

• Use style_profile.md as structural guidance only. Match section-count tendency, theorem density, caption-length distribution, sentence cadence, math display ratio, citation style.
• Never copy prose, claims, examples, or terminology from anything reachable through the cache.
• Never pass — style-ref (or the cache contents) to reviewer / auditor sub-skills — Phase 4.5 (/proof-checker), Phase 4.7 / 5.5 (/paper-claim-audit), Phase 5 (/auto-paper-improvement-loop reviewer), Phase 5.8 (/citation-audit) MUST run on the artifact alone. Cross-model review independence (../shared-references/reviewer-independence.md).

Pipeline

Phase 0: Assurance Setup

Resolve the active assurance level and persist it so Phase 6's external verifier reads the same value. Run once at pipeline start, before Phase 1.

Resolution order (first match wins):

1. Explicit — assurance: draft | submission in $ARGUMENTS
2. Derived from — effort:

• lite / balanced → draft (default, zero change from current behavior)
• max / beast → submission

1. Default: draft

Action:

mkdir -p paper/.aris
echo "" > paper/.aris/assurance.txt   # draft or submission

What each level does downstream:

• draft — Existing behavior. Audits run only when their content detector

matches (Phase 4.5 / 4.7 / 5.5 / 5.8). Missing artifacts are non-blocking. Silent-skip allowed.

• submission — The three mandatory audits (proof-checker,

paper-claim-audit, citation-audit) are treated as load-bearing gates. Each sub-audit must emit its JSON artifact (PASS / WARN / FAIL / NOT_APPLICABLE / BLOCKED / ERROR) — never silent-skip. Phase 6 runs tools/verify_paper_audits.sh; a non-zero exit blocks the Final Report.

Escape hatch: a user wanting the old "beast = depth-only, no audit gate" can pass — effort: beast, assurance: draft explicitly. Legal but discouraged for actual submissions. See shared-references/assurance-contract.md for the full contract.

Announce the resolved level in-line before Phase 1:

📋 Assurance:  (derived from effort: )
   

Phase 1: Paper Plan

Invoke /paper-plan to create the structural outline:

/paper-plan "$ARGUMENTS"

If — style-ref: was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: to the invocation: /paper-plan " — style-ref: ". (Writer-side phase — forwarding is allowed; reviewer/auditor phases below must not see the style ref.)

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

If — style-ref: was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: to every writer-side sub-skill invocation in this pipeline (Phases 1, 2b, 3, 5). Do not append it to reviewer/auditor invocations (Phases 4.5, 4.7, 5.5, 5.8).

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: paper-figure covers data plots and comparison tables. Architecture diagrams, pipeline figures, and method illustrations are handled in Phase 2b below.

Phase 2b: Architecture & Illustration Generation

Skip this step entirely if illustration: false.

If the paper plan includes architecture diagrams, pipeline figures, audit cascades, or method illustrations, invoke the appropriate generator based on the illustration parameter:

When illustration: figurespec (default) — invoke /figure-spec:

/figure-spec "[architecture/workflow description from PAPER_PLAN.md]"

• Deterministic JSON → SVG vector rendering (editable, reproducible)
• Best for: system architecture, workflow pipelines, audit cascades, layered topology
• Output: figures/*.svg + figures/*.pdf (via rsvg-convert) + figures/specs/*.json
• No external API, runs fully local

If — style-ref: was passed and the helper succeeded above, append — style-ref: to the invocation below as well.

When illustration: gemini — invoke /paper-illustration:

/paper-illustration "[method description from PAPER_PLAN.md or NARRATIVE_REPORT.md]"

• Claude plans → Gemini optimizes → Nano Banana Pro renders → Claude reviews (score ≥ 9)
• Best for: qualitative method illustrations, natural-style diagrams, result grids
• Output: figures/ai_generated/*.png
• Requires GEMINI_API_KEY environment variable

When illustration: mermaid — invoke /mermaid-diagram:

/mermaid-diagram "[method description from PAPER_PLAN.md]"

• Generates Mermaid syntax diagrams (flowchart, sequence, class, state, etc.)
• Best for: lightweight flowcharts, state machines, simple sequence diagrams
• Output: figures/*.mmd + figures/*.png
• Free, no API key needed

When illustration: codex-image2 — invoke /paper-illustration-image2:

/paper-illustration-image2 "[method description from PAPER_PLAN.md or NARRATIVE_REPORT.md]"

• Claude plans → Codex native image generation renders → Claude reviews (same multi-stage workflow as gemini, different renderer)
• Best for: users who want a GPT-image-style renderer without needing GEMINI_API_KEY; uses your existing Codex / ChatGPT Plus/Pro quota
• Output: figures/ai_generated/figure_final.png + latex_include.tex + review_log.json (emitted via tools/paper_illustration_image2.py finalize)
• Prerequisites (beyond ARIS's standard Claude Code + Codex coexistence): the local Codex app-server must be signed in (codex debug app-server send-message-v2 "ping" succeeds), and the dedicated MCP bridge must be registered — see mcp-servers/codex-image2/README.md for the one-time claude mcp add command. Run python3 tools/paper_illustration_image2.py preflight --workspace . to confirm before relying on this path.
• Experimental: this renderer shells through the Codex debug app-server, which Codex documents as an unstable surface. Prefer figurespec or gemini for production submission flows until codex-image2 stabilizes.

When illustration: false — skip entirely. All non-data figures must be created manually (draw.io, Figma, TikZ) and placed in figures/ before Phase 3.

Choosing the right mode:

• Formal architecture / workflow / topology figures → figurespec (default)
• Method concept illustrations with natural style, have GEMINI_API_KEY → gemini
• Method concept illustrations, prefer ChatGPT Plus/Pro quota over Gemini key → codex-image2
• Quick flowchart / state machine → mermaid
• Full manual control → false

These are complementary, not mutually exclusive: you can run multiple generators for different figures in the same paper by re-invoking with different illustration overrides.

Checkpoint: List generated vs manual figures.

📊 Figures complete:
- Data plots (auto, Phase 2): [list]
- Architecture/illustrations (auto, Phase 2b, mode=): [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"

If — style-ref: was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: to the invocation: /paper-write "PAPER_PLAN.md — style-ref: ".

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 4.5: Proof Verification (theory papers only)

Skip this phase if the paper contains no theorems, lemmas, or proofs.

if paper contains \begin{theorem} or \begin{lemma} or \begin{proof}:
    Run /proof-checker "paper/"
    This invokes GPT-5.4 xhigh to:
    - Verify all proof steps (hypothesis discharge, interchange justification, etc.)
    - Check for logic gaps, quantifier errors, missing domination conditions
    - Attempt counterexamples on key lemmas
    - Generate PROOF_AUDIT.md with issue list + severity

    If FATAL or CRITICAL issues found:
        Fix before proceeding to improvement loop
    If only MAJOR/MINOR:
        Proceed, improvement loop may address remaining issues
else:
    skip — no proofs, no action

Phase 4.7: Paper Claim Audit

Skip if no result files exist (e.g., survey/position papers with no experiments).

if results/*.json or results/*.csv or outputs/*.json exist:
    Run /paper-claim-audit "paper/"
    Fresh zero-context reviewer compares every number in the paper
    against raw result files. Catches rounding inflation, best-seed
    cherry-pick, config mismatch, delta errors.

    If FAIL:
        Fix mismatched numbers before improvement loop
    If WARN:
        Proceed, but flag for manual verification
else:
    skip — no experimental results to verify

Phase 5: Auto Improvement Loop

Invoke /auto-paper-improvement-loop to polish the paper:

/auto-paper-improvement-loop "paper/"

If — style-ref: was passed in $ARGUMENTS and the h

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: raja21068
• Source: raja21068/AutoResearch
• License: MIT

Install and usage instructions live in the source repository linked above.