paper-writing
Skill2 starsChanged 6 months agoMITView on GitHub
Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → figure-spec/paper-illustration/mermaid-diagram → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished PDF. At `— effort: max | beast` (or explicit `— assurance: submission`), Phase 6 gates the Final Report on `tools/verify_paper_audits.sh`; the PDF is labelled `submission-ready` only when the external verifier is green. 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.
- Reads credentials
We split this skill into the rules it gives an agent
30 rules. 0 are common, 11 are distinctive, and 19 are very specific to this project.
0
Common
Most of the 24 edited versions we read keep these.
11
Distinctive
This author's own choices. Worth a look.
19
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 51
When — style-ref: <source> is in $ARGUMENTS, run the helper FIRST, before Phase 1 (paper-plan):
- Very specific: line 76
Use style_profile.md as structural guidance only.
- Very specific: line 133
If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: …
- Very specific: line 162
If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to every writer-side …
- Very specific: line 171
Read figure plan from PAPER_PLAN.md
- Very specific: line 174
Create figures/latex_includes.tex for easy insertion
- Very specific: line 185
If the paper plan includes architecture diagrams, pipeline figures, audit cascades, or method illustrations, invoke the appropriate …
- Distinctive: line 194
No external API, runs fully local
- Very specific: line 196
If — style-ref: <source> was passed and the helper succeeded above, append — style-ref: <source> to the invocation below as well.
- Very specific: line 258
If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: …
- Distinctive: line 261
Write each section following the plan, with proper LaTeX formatting
- Very specific: line 361
If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: …
- Distinctive: line 372
Add missing interpretations and notation
- Distinctive: line 374
Add theory-aligned experiments if needed
- Very specific: line 382
After /auto-paper-improvement-loop finishes, rerun /paper-claim-audit before the final report whenever the paper contains numeric claims …
- Distinctive: line 384
Use the same detectors as Phase 4.7:
- Distinctive: line 389
If numeric claims exist but no raw result files are found, stop and warn the user before declaring the paper complete.
- Distinctive: line 390
If no numeric claims exist, skip.
- Very specific: line 441
After the final paper-claim-audit passes, run /citation-audit to verify every \cite{...} along three axes: existence, metadata correctness, …
- Very specific: line 475
Before writing the Final Report, resolve the active assurance level.
- Very specific: line 489
Read paper/.aris/assurance.txt.
- Very specific: line 491
If the file's value disagrees with the derived level (e.g.
- Distinctive: line 495
Use the re-derived level as authoritative for the rest of Phase 6.
- Very specific: line 504
If ASSURANCE=draft, skip directly to the Final Report template below —
- Very specific: line 507
If ASSURANCE=submission, run the pre-flight checklist below, then the verifier.
- Very specific: line 657
Large file handling: If the Write tool fails due to file size, immediately retry using Bash (cat << 'EOF' > file) to write in chunks.
- Very specific: line 659
Checkpoint between phases: when AUTO_PROCEED=false. Present results and wait for approval.
- Distinctive: line 660
Manual figures first: If the paper needs architecture diagrams or qualitative results, the user must provide them before Phase 3.
- Distinctive: line 661
Compilation must succeed: before entering the improvement loop.
- Distinctive: line 664
Respect page limits: If the paper exceeds the venue limit, suggest specific cuts before the improvement loop.
“Common” is measured: kept by at least 6 in 10 of the 24 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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. - 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
falseto 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. Whenfalse(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; needsGEMINI_API_KEY),codex-image2(AI-generated via/paper-illustration-image2through 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), orfalse(skip Phase 2b, manual only).
Override inline:
/paper-writing "NARRATIVE_REPORT.md" — venue: NeurIPS, illustration: gemini, human checkpoint: trueIEEE example:/paper-writing "NARRATIVE_REPORT.md" — venue: IEEE_JOURNAL
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.
Optional: Style reference (— style-ref: <source>, 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: <source> 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 "<source>")
case $? in
0) ;; # share $CACHE/style_profile.md with downstream WRITER phases only
2) echo "warning: style-ref skipped (missing optional dep)" >&2 ;;
3) echo "error: --style-ref source failed; aborting pipeline" >&2 ; exit 1 ;;
*) echo "error: helper failed unexpectedly; aborting pipeline" >&2 ; exit 1 ;;
esacThen forward — style-ref: <source> only to the writer-side sub-skills:
/paper-plan(Phase 1) — outline structure/paper-write(Phase 3) — section-by-section prose/paper-illustration(Phase 2b) — figure structural matching, optional
Sources accepted: local TeX dir / file, local PDF, arXiv id, http(s) URL. Overleaf URLs/IDs are rejected — clone via /overleaf-sync setup <id> first and pass the local clone path.
Strict rules (full contract in tools/extract_paper_style.py docstring):
- Use
style_profile.mdas structural guidance only. Match section-count tendency, theorem density, caption-length distribution, sentence cadence, math display ratio, citation style. - Never copy prose, claims, examples, or terminology from anything reachable through the cache.
- Never pass
— style-ref(or the cache contents) to reviewer / auditor sub-skills — Phase 4.5 (/proof-checker), Phase 4.7 / 5.5 (/paper-claim-audit), Phase 5 (/auto-paper-improvement-loopreviewer), Phase 5.8 (/citation-audit) MUST run on the artifact alone. Cross-model review independence (../shared-references/reviewer-independence.md).
Pipeline
Phase 0: Assurance Setup
Resolve the active assurance level and persist it so Phase 6's external
verifier reads the same value. Run once at pipeline start, before Phase 1.
Resolution order (first match wins):
- Explicit
— assurance: draft | submissionin$ARGUMENTS - Derived from
— effort:lite/balanced→draft(default, zero change from current behavior)max/beast→submission
- Default:
draft
Action:
mkdir -p paper/.aris
echo "<resolved-level>" > paper/.aris/assurance.txt # draft or submissionWhat 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 runstools/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: <level> (derived from effort: <effort>)
<either "current behavior, no audit gate" OR "mandatory audits gated by tools/verify_paper_audits.sh">Phase 1: Paper Plan
Invoke /paper-plan to create the structural outline:
/paper-plan "$ARGUMENTS"If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: /paper-plan "<topic> — style-ref: <source>". (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: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> 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.texfor easy insertion - GPT-5.4 reviews figure quality and captions
Output: figures/ directory with PDFs, generation scripts, and LaTeX snippets.
Scope:
paper-figurecovers 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: <source> was passed and the helper succeeded above, append — style-ref: <source> 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_KEYenvironment 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 viatools/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 — seemcp-servers/codex-image2/README.mdfor the one-timeclaude mcp addcommand. Runpython3 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
figurespecorgeminifor production submission flows untilcodex-image2stabilizes.
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=<illustration>): [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: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: /paper-write "PAPER_PLAN.md — style-ref: <source>".
What this does:
- Write each section following the plan, with proper LaTeX formatting
- Insert figure/table references from
figures/latex_includes.tex - Build
references.bibfrom 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 -pdfwith 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 actionPhase 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 verifyPhase 5: Auto Improvement Loop
Invoke /auto-paper-improvement-loop to polish the paper:
/auto-paper-improvement-loop "paper/"If — style-ref: <source> was passed in $ARGUMENTS and the helper succeeded above, append — style-ref: <source> to the invocation: /auto-paper-improvement-loop "paper/ — style-ref: <source>". The improvement loop's reviewer sub-agent will still NOT see the style ref (the loop's own SKILL forbids it); only the fix-implementation phase consumes it.
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. Location-aware thresholds: any main-body overfull blocks completion regardless of size; appendix overfulls block only if >10pt; bibliography overfulls block only if >20pt.
Phase 5.5: Final Paper Claim Audit (MANDATORY submission gate)
After /auto-paper-improvement-loop finishes, rerun /paper-claim-audit before the final report whenever the paper contains numeric claims and machine-readable raw result files exist.
Use the same detectors as Phase 4.7:
- numeric-claim regex over
paper/main.texandpaper/sections/*.tex - raw-evidence file search in
results/,outputs/,experiments/, andfigures/for.json,.jsonl,.csv,.tsv,.yaml, or.yml
This phase is mandatory if both detectors are positive. It blocks the final report. If numeric claims exist but no raw result files are found, stop and warn the user before declaring the paper complete. If no numeric claims exist, skip.
NUMERIC_CLAIMS=$(rg -n -e '[0-9]+(\.[0-9]+)?\s*(%|\\%|±|\\pm|x|×)' \
-e '(accuracy|BLEU|F1|AUC|mAP|top-1|top-5|error|loss|perplexity|speedup|improvement)' \
paper/main.tex paper/sections 2>/dev/null || true)
RAW_RESULT_FILES=$(find results outputs experiments figures -type f \
\( -name '*.json' -o -name '*.jsonl' -o -name '*.csv' -o -name '*.tsv' -o -name '*.yaml' -o -name '*.yml' \) 2>/dev/null | head -200)
if [ -n "$NUMERIC_CLAIMS" ] && [ -n "$RAW_RESULT_FILES" ]; then
Run /paper-claim-audit "paper/"
If FAIL:
Fix mismatched numbers before the final report
elif [ -n "$NUMERIC_CLAIMS" ]; then
Stop and warn: the paper contains numeric claims but no raw evidence files were found
fiEmpirical motivation: in a real submission run, the final paper claimed a narrower experiment grid than the raw JSON actually contained, and a tolerance value was rounded down past the actual relative error. Both were caught only after manual paper-claim-audit invocation in the final round; the improvement loop did not detect them.
Phase 5.6: Kill-Argument Adversarial Review (theory / scope-heavy papers)
After Phase 5.5 (claim audit) passes, run /kill-argument whenever the paper is theory-heavy or makes explicit scope/generality claims in the title or abstract. This is a final adversarial check that complements the claim/citation/proof audits: those verify local correctness (numbers match, cites resolve, theorems prove); kill-argument tests headline-level survival — whether the paper as a whole answers the worst rejection paragraph a senior area chair would write.
THEORY_ENV_COUNT=$(rg -c '\\begin\{(theorem|lemma|proposition|corollary)\}' paper/main.tex paper/sections 2>/dev/null | awk -F: '{s+=$2} END {print s+0}')
SCOPE_HINT=$(rg -i 'general(ization)?|broad|universal|across|any [A-Za-z]+ model|holds for' paper/sections/0*abstract* 2>/dev/null | head -1)
if [ "$THEORY_ENV_COUNT" -ge 5 ] || [ -n "$SCOPE_HINT" ]; then
/kill-argument "paper/"
KILL_VERDICT=$(jq -r '.verdict' paper/KILL_ARGUMENT.json)
KILL_REASON=$(jq -r '.reason_code' paper/KILL_ARGUMENT.json)
fiGating (depends on the resolved assurance level from Phase 0):
| Assurance level | THEORY/SCOPE detected | Behavior |
submission | yes | MANDATORY. FAIL blocks the final report; WARN requires explicit user acknowledgment; BLOCKED/ERROR blocks the final report (cannot ship without an adversarial pass). |
submission | no | Skip — KILL_ARGUMENT.json is written with verdict: NOT_APPLICABLE, reason_code: not_theory_or_scope_paper so the submission verifier sees a record. |
internal / draft | yes | Advisory. Run if the user passed — kill-argument: true; otherwise skip. WARN/FAIL is logged but does not block. |
internal / draft | no | Skip. |
/kill-argument itself never edits the paper; it writes KILL_ARGUMENT.{md,json}. If still_unresolved critical points are surfaced, queue them for the next /auto-paper-improvement-loop round (Step 5.5 of that skill auto-merges the findings into its fix list).
Why this is the right place: Phase 5 (loop) optimizes for score, Phase 5.5 (claim audit) verifies numbers, Phase 5.8 (citation audit) verifies cites — none of these catches the case where every local component is correct but the paper still oversells what it actually proves. Kill-argument is the dedicated headline-scope check.
Phase 5.8: Citation Audit (submission gate)
After the final paper-claim-audit passes, run /citation-audit to verify every \cite{...} along three axes: existence, metadata correctness, and context appropriateness. This is the fourth and final layer of the evidence-and-claim assurance stack (experiment-audit → result-to-claim → paper-claim-audit → citation-audit).
if paper/references.bib (or paper.bib) exists and contains entries cited from sec/*.tex:
Run /citation-audit "paper/"
Fresh cross-family reviewer (gpt-5.4 via Codex MCP) with web/DBLP/arXiv lookup
verifies each entry:
(i) EXISTENCE — paper resolves at claimed arXiv ID / DOI / venue
(ii) METADATA — author names, year, venue, title match canonical sources
(iii) CONTEXT — cited paper actually establishes the claim it supports
Output:
- CITATION_AUDIT.md (human-readable per-entry verdict report)
- CITATION_AUDIT.json (machine-readable verdict ledger)
- Per-entry verdicts: KEEP / FIX / REPLACE / REMOVE
If any REPLACE or REMOVE verdicts:
Surface to user for human approval — never auto-modify content claims
If only FIX verdicts (metadata corrections):
Apply with user confirmation, then recompile
If all KEEP:
Pass — bibliography clean for submission
else:
skip — no bib file or no citationsWhy this is the most diagnostic of the four audit layers: wildly fake citations are easy to spot. The dangerous failure mode is a real paper used to support a claim it does not actually establish (wrong-context citations) — these slip past metadata-only checks and damage submission credibility. Run cost is wall-clock heavy (web lookup per entry); run once per submission, not per save.
Empirical motivation: in a real submission run, several real papers were cited in contexts they did not actually support, and at least one bib entry shipped with author = "Anonymous" because the metadata had not been resolved. None were caught by the improvement loop or numeric claim audit; only fresh web-lookup review surfaced them.
Phase 6: Final Report
Phase 6.0 — Submission Gate
Before writing the Final Report, resolve the active assurance level. This
uses the same derivation rule as Phase 0 so a run where Phase 0 was
skipped or its write failed cannot silently downgrade a beast / max /
— assurance: submission invocation back to draft.
Resolution at the gate (re-derive; do not trust .aris/assurance.txt
alone):
- Parse
$ARGUMENTSfor an explicit— assurance: draft | submissionor an— effort: lite | balanced | max | beastdirective. - Derive the expected level:
- explicit
assurance:wins - else
lite/balanced→draft,max/beast→submission - else
draft
- explicit
- Read
paper/.aris/assurance.txt. If the file is missing, write it now with the derived level. - If the file's value disagrees with the derived level (e.g. file
says
draftbut$ARGUMENTSsaysbeast), overwrite the file with the derived level and surface a one-line warning in-chat:⚠️ .aris/assurance.txt was draft but $ARGUMENTS says submission; overriding. - Use the re-derived level as authoritative for the rest of Phase 6.
# Final authoritative value, written and read from the same source
ASSURANCE=<derived-from-$ARGUMENTS> # draft | submission
mkdir -p paper/.aris
echo "$ASSURANCE" > paper/.aris/assurance.txtIf ASSURANCE=draft, skip directly to the Final Report template below —
current behavior, no change for the default balanced user.
If ASSURANCE=submission, run the pre-flight checklist below, then the
verifier. The verifier's exit code is the source of truth — do NOT
self-declare "audits complete" based on conversation memory.
Submission pre-flight checklist
Print this checklist verbatim at the start of Phase 6.0 and confirm each row before proceeding. This resists the common failure mode of the model skipping audits while claiming to have run them.
📋 Submission audits required before Final Report:
[ ] 1. /proof-checker → paper/PROOF_AUDIT.json
[ ] 2. /paper-claim-audit → paper/PAPER_CLAIM_AUDIT.json
[ ] 3. /citation-audit → paper/CITATION_AUDIT.json
[ ] 4. bash <ARIS_REPO>/tools/verify_paper_audits.sh paper/ --assurance submission
[ ] 5. Block Final Report iff verifier exit code != 0
<ARIS_REPO>placeholder — replace with the absolute path to your ARIS clone (e.g.~/Desktop/Auto-claude-code-research-in-sleepor the path returned bydirname $(readlink ~/.claude/skills/paper-writing/SKILL.md)/../..). The path is stable across runs; store it in a shell variable if you prefer (export ARIS_REPO=~/…and use"$ARIS_REPO"in the command).
Invoking the three audits
Each sub-audit runs in a fresh Codex thread (never codex-reply,
never pass prior audit output as context — this preserves reviewer
independence per shared-references/reviewer-independence.md).
Each sub-audit always emits its JSON artifact, even when the content
detector is negative. A detector-negative run emits verdict
NOT_APPLICABLE; a silent skip is forbidden. See the "Submission artifact
emission" section of each audit's SKILL.md.
Order:
/proof-checker "paper/"→ writespaper/PROOF_AUDIT.json(emitsNOT_APPLICABLEif the paper contains no theorems / lemmas / proofs)/paper-claim-audit "paper/"→ writespaper/PAPER_CLAIM_AUDIT.json(emitsNOT_APPLICABLEif the paper has no numeric claims; emitsBLOCKEDif numeric claims exist but raw result files are missing)/citation-audit "paper/"→ writespaper/CITATION_AUDIT.json(emitsNOT_APPLICABLEif no.bibfile or no\cite{...}usage)
Running the verifier
bash <ARIS_REPO>/tools/verify_paper_audits.sh paper/ --assurance submission- Exit 0 — All mandatory audits present, JSON schema-valid, hashes fresh, no blocking verdicts. Proceed to the Final Report below.
- Exit 1 — Surface
paper/.aris/audit-verifier-report.jsonto the user verbatim, refuse to generate the Final Report, and list the specific remediation for each failing row:MISSING→ rerun that auditSTALE→ paper files edited after the audit ran; rerun the affected auditBLOCKING_VERDICT(FAIL / BLOCKED / ERROR) → fix the underlying issue, then rerun the auditSCHEMA_INVALID→ audit artifact malformed; rerun the audit
The verifier is cheap to rerun (< 1 s). After fixing any issue, rerun it before claiming green.
Optional hardening (not default)
Teams that want hook-level enforcement — i.e., the harness physically
prevents a Stop event while the verifier is red — can register a Stop hook
in ~/.claude/settings.json:
{
"hooks": {
"Stop": [
{"command": "bash <ARIS_REPO>/tools/verify_paper_audits.sh paper/ --assurance submission"}
]
}
}This is documented here, not required. Phase 6.0's verifier-as-truth pattern is the default repo behavior.
Phase 6.1 — Final Report (runs only after the submission gate is green,
or directly if assurance=draft)
# Paper Writing Pipeline Report
**Input**: [NARRATIVE_REPORT.md or topic]
**Venue**: [ICLR/NeurIPS/ICML/CVPR/ACL/AAAI/ACM/IEEE_JOURNAL/IEEE_CONF]
**Assurance**: [draft | submission]
**Submission-ready**: [yes | no] <!-- yes iff assurance=submission AND verifier exit 0 -->
**Date**: [today]
## Pipeline Summary
| Phase | Status | Output |
|-------|--------|--------|
| 0. Assurance Setup | ✅ | paper/.aris/assurance.txt = [draft\|submission] |
| 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 |
| 4.5 Proof Audit | [PASS\|WARN\|FAIL\|NOT_APPLICABLE\|BLOCKED\|ERROR] | PROOF_AUDIT.{md,json} |
| 5.5 Paper Claim Audit | [PASS\|WARN\|FAIL\|NOT_APPLICABLE\|BLOCKED\|ERROR] | PAPER_CLAIM_AUDIT.{md,json} |
| 5.8 Citation Audit | [PASS\|WARN\|FAIL\|NOT_APPLICABLE\|BLOCKED\|ERROR] | CITATION_AUDIT.{md,json} |
| 6.0 Assurance Verifier | [OK\|STALE\|BLOCKING_VERDICT\|HAS_ISSUES\|SCHEMA_INVALID\|MISSING] per audit; exit [0\|1] overall (N/A if draft) | .aris/audit-verifier-report.json |
## 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
- paper/PROOF_AUDIT.{md,json} — Proof-obligation verification (always emitted at `assurance=submission`; `NOT_APPLICABLE` when no theorems)
- paper/PAPER_CLAIM_AUDIT.{md,json} — Numerical claim verification (always emitted at `assurance=submission`; `NOT_APPLICABLE` when no numeric claims; omitted in `draft` mode if Phase 5.5 detector was negative)
- paper/CITATION_AUDIT.{md,json} — Bibliography verification (always emitted at `assurance=submission`; `NOT_APPLICABLE` when no `.bib` or no `\cite{...}`; omitted in `draft` mode if Phase 5.8 detector was negative)
- paper/.aris/audit-verifier-report.json — External verifier report (submission only)
## 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 / HotCRPOutput Protocols
Follow these shared protocols for all output files:
- Output Versioning Protocol — write timestamped file first, then copy to fixed name
- Output Manifest Protocol — log every output to MANIFEST.md
- Output Language Protocol — note: paper-writing always outputs English LaTeX for venue submission
Key Rules
- Large file handling: If the Write tool fails due to file size, immediately retry using Bash (
cat << 'EOF' > file) to write in chunks. Do NOT ask the user for permission — just do it silently. - 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.
Other versions34 projects use a version of this.
Word for word · 1
- Chanw-research/claude-code-paper-writing★ 42100% same
Edited · 6
- wanshuiyin/Auto-claude-code-research-in-sleep★ 18k50% same
- catalsqlb-cmd/Prism-H★ 1677% same
- Yulivu/debuffer-skills★ 948% same
- Yusong-Enceladus/claude-skills★ 861% same
- Shri-Phnx/claude-skills★ 222% same
- talhaMah56/claude_skills★ 054% same
Wrote their own version · 27
- getcompanion-ai/feynman★ 10ksame name
- advaitpaliwal/feynman★ 10ksame name
- companion-inc/feynman★ 10ksame name
- MLNLP-World/Paper-Writing-Tips★ 4.7ksame name
- ZimoLiao/scholaraio★ 577same name
- EvoScientist/EvoSkills★ 481same name
- SNL-UCSB/paper-writing-skill★ 181same name
- voidful/academic-skills★ 126same name
- TenureAI/PhD-Zero★ 52same name
- HughYau/pengsida-learning-research-skills★ 27same name
17 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use ml-training-recipe, replication and 5 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
advaitpaliwalSkillml-training-recipe
Find implementable ML training recipes from papers, datasets, docs, and code. Use when the user wants to fine-tune, train, reproduce, or choose a practical ML method, dataset, hyperparameter setup, or benchmark recipe.
Also in 3 projects that use this
advaitpaliwalSkillreplication
Plan a replication of a paper, claim, or benchmark, and execute only after an explicit environment choice. Use when the user asks to replicate results, reproduce an experiment, verify a claim empirically, or build a replication package.
Also in 3 projects that use this
JimLiuSkillpdf-explore
Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers — including appendices). Skip it only for a single lookup of 1–4 pages quoted in your very next response — `read_file(pages=[...])` attaches pages as images that are dropped from context after one turn, so multi-section answers end up re-reading the same ranges repeatedly. Parses the PDF once in the Python kernel: `pdf_pages` (pages as persistent text), `pdf_outline` (TOC), `pdf_scan` (rank pages by relevance), `pdf_map`/`pdf_extract` (per-page summary / structured fields via parallel haiku calls). For PDF creation/manipulation, use reportlab/pypdf directly.
Also in 4 projects that use this
JaimeParkerSkillpaper-code-audit
Perform three-way cross-validation of a research paper by comparing the original paper text (via Zotero), official code implementation (via Git), and personal Obsidian notes. Use this skill whenever the user wants to "audit a paper", "verify paper claims against code", "cross-check notes with implementation", "triangulate paper + code + notes", "find discrepancies between paper and code", or mentions wanting a deep, structured comparison of a paper's claims against its implementation and their own notes. Also trigger when the user asks to "analyze this paper thoroughly" with code available, or when they want to systematically reconcile what the paper says, what the code does, and what their notes claim.
Also in 3 projects that use this
brainbytes-devSkillalpha-research
Also in 3 projects that use this
luischanciSkillresearch-ideation
Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset.
Also in 3 projects that use this
- +1 more from advaitpaliwal
In this repository84 other files it gives its agents.
- skills/rules/common/agents.mdAGENTS.md
- skills/rules/zh/agents.mdAGENTS.md
- ablation-plannerSkill
- alphaxivSkill
- analyze-resultsSkill
- arxivSkill
- auto-paper-improvement-loopSkill
- auto-review-loop-llmSkill
- auto-review-loop-minimaxSkill
- auto-review-loopSkill
- citation-auditSkill
- claims-draftingSkill
- comm-lit-review-claude-singleSkill
- deepxivSkill
- dse-loopSkill
- embodiment-descriptionSkill
- exa-searchSkill
- experiment-auditSkill
- experiment-bridgeSkill
- experiment-planSkill
- experiment-queueSkill
- feishu-notifySkill
- figure-descriptionSkill
- figure-specSkill
- formula-derivationSkill
- gemini-searchSkill
- grant-proposalSkill
- idea-creatorSkill
- idea-discovery-robotSkill
- idea-discoverySkill
- invention-structuringSkill
- jurisdiction-formatSkill
- kill-argumentSkill
- mermaid-diagramSkill
- meta-optimizeSkill
- monitor-experimentSkill
- novelty-checkSkill
- openalexSkill
- overleaf-syncSkill
- paper-claim-auditSkill
- paper-compileSkill
- paper-figureSkill
- paper-illustration-image2Skill
- paper-illustrationSkill
- paper-planSkill
- paper-posterSkill
- paper-slidesSkill
- paper-talkSkill
- paper-writeSkill
- patent-novelty-checkSkill
- patent-pipelineSkill
- patent-reviewSkill
- pixel-artSkill
- prior-art-searchSkill
- proof-checkerSkill
- proof-writerSkill
- qzcliSkill
- rebuttalSkill
- research-litSkill
- research-pipelineSkill
- The first 60 shown.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

