paper-review-pipeline

تایید شده

Use when a mostly complete ML conference paper needs self-review, pre-submission QA, camera-ready checking, section-by-section critique, citation-risk inspection, or rebuttal/review-response drafting. Skip this for initial drafting and use `paperreview` only when the user explicitly wants external submission.

@cnfjlhj
MIT۱۴۰۵/۲/۲۱
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نصب مهارت

مهارت‌ها کدهای شخص ثالث از مخازن عمومی GitHub هستند. SkillHub الگوهای مخرب شناخته‌شده را اسکن می‌کند اما نمی‌تواند امنیت را تضمین کند. قبل از نصب، کد منبع را بررسی کنید.

نصب سراسری (سطح کاربر):

npx skillhub install cnfjlhj/ai-collab-playbook/paper-review-pipeline

نصب در پروژه فعلی:

npx skillhub install cnfjlhj/ai-collab-playbook/paper-review-pipeline --project

مسیر پیشنهادی: ~/.claude/skills/paper-review-pipeline/

محتوای SKILL.md

---
name: paper-review-pipeline
description: Use when a mostly complete ML conference paper needs self-review, pre-submission QA, camera-ready checking, section-by-section critique, citation-risk inspection, or rebuttal/review-response drafting. Skip this for initial drafting and use `paperreview` only when the user explicitly wants external submission.
---

# Paper Review Pipeline (ML Top Conferences)

Run a *two-view* paper review for ML conference submissions:

1) **Section-by-section review** (Abstract → Intro → Method → Experiments → …) with concrete edits.
2) **Prioritized issue list** with **P0/P1/P2** severity, grouped by category, including recommended fixes and verification notes.

This skill also supports **rebuttal / review response**: parse reviewer comments, classify, choose a strategy, and draft a professional point-by-point response.

## Parity Guarantee (No-Omission)

This skill is a consolidation layer. It must **not** omit any distinctive workflow, constraints, or output formats from the legacy skills it replaces.

Use:
- `references/parity-matrix.md` as the feature-parity contract and regression scenarios.
- `references/modules/` for full imported workflows and checklists.

## Execution Modes

This skill supports two modes:

- **Default: `targeted`** — run only the most relevant tracks based on the user request and inputs, but **always** produce the Final Synthesis.
- **Optional: `full-parallel`** — run **all tracks** as independent outputs (acceptable redundancy), then produce the Final Synthesis.

Trigger `full-parallel` when the user says: “全量”, “并行”, “run all tracks”, “run every skill”, “逐个 skill 测试”, “full pipeline”.

Protocol + required report template:
- `references/full-parallel-protocol.md`
- `references/report-template.md`

## Optional External Second Opinion (`paperreview`)

If the user provides a near-final or final PDF, complete the local review first and then explicitly ask whether they also want an external second opinion via `paperreview`.

- Ask only when the input is clearly a near-final or final PDF.
- Do **not** auto-submit to external services. Get explicit confirmation first.
- If the user agrees, hand off to `paperreview` as a follow-up step; otherwise finish with the local pipeline result only.

## When to Use

- Pre-submission quality check (ICML/ICLR/NeurIPS/AAAI).
- After a draft is “mostly done” but clarity/logic is shaky.
- When you suspect citation problems (missing, inconsistent, unverified, or claim-to-citation mismatch).
- Before sending to advisor/collaborators for feedback (to reduce “obvious issues”).
- After receiving reviews: draft rebuttal and a revision plan.

## When NOT to Use

- If the user wants **new research** or **new experiments** invented: require the user to provide results/artifacts.
- If the user asks for **verbatim PDF-to-LaTeX copying** or large-scale reformatting without source.
- If the task is **pure BibTeX generation from memory**: do not do it; use verified metadata workflows.

## Non-Negotiable Guardrails

1) **No hallucinated citations.**
   - If a citation cannot be verified, mark it as `[CITATION NEEDED]` / placeholder and tell the user explicitly.
   - Do not fabricate authors/years/venues/DOIs.
2) **Do not change technical meaning.**
   - When proposing edits, preserve claims and numbers unless the user provides corrected data.
3) **Preserve LaTeX semantics when editing source.**
   - Do not break `\\cite{}`, `\\ref{}`, `\\label{}`, math environments, figures/tables, or bibliography hooks.
4) **Respect blind review constraints (if applicable).**
   - Avoid identity-revealing self-citations, acknowledgments, or repo links unless the user confirms it is camera-ready.

## Inputs (Ask for the Minimum Needed)

### For pre-submission review
- Paper source: LaTeX section text, or the relevant excerpts pasted in chat (preferred), and optionally the PDF for context.
- Target venue + track (ICML/ICLR/NeurIPS/AAAI) and any required sections (e.g., limitations / broader impact / ethics).
- One-sentence contribution (if the user has it). If not, infer and ask for confirmation.

### For rebuttal / review response
- Reviewer comments (verbatim text, ideally grouped by reviewer).
- Rebuttal constraints: word/page limit, formatting (ICLR OpenReview vs PDF), and timeline.
- What the user is willing to change: “clarify only” vs “add experiments” vs “major rewrite”.

## Output Contract (Always Produce Both Views)

### View A — Section-by-Section Review

For each section, output:
- **What works** (1–3 bullets)
- **What’s missing / unclear** (P0/P1/P2 tagged bullets)
- **Concrete fixes** (rewrite suggestions or structural moves)

Use the checklists in:
- `references/section-review-checklist.md`

### View B — P0/P1/P2 Issue List (Prioritized)

Format each issue like:
- **Priority**: P0 (blocking) / P1 (important) / P2 (nice-to-have)
- **Category**: Narrative / Evidence / Experimental Design / Statistics / Reproducibility / Citations / Writing / Figures-Tables / Format
- **Where**: section name + a short quote anchor (or LaTeX label if available)
- **Problem**
- **Fix**
- **Verification** (if needed): what evidence/log/search is required before claiming it is correct

Use the taxonomy in:
- `references/p0-p2-taxonomy.md`

## Modules (Routing Rules)

Use these modules to preserve legacy feature parity:

- **Paper-level QA**: `references/modules/paper-self-review.md`
- **Rebuttal / review response**: `references/modules/review-response.md` and `references/rebuttal-workflow.md`
- **LaTeX + BibTeX toolbox**: `references/modules/academic-paper-helper.md`
- **Claim-level citation audit**: `references/modules/citation-validator.md` and `references/citation-integrity.md`
- **Anti-AI polish**: `references/modules/writing-anti-ai.md`
- **LaTeX rhythm pass**: `references/modules/latex-rhythm-refiner.md`
- **Literature discovery (extended)**: `references/modules/claude-scholar-ml-paper-writing.md`

## Workflow (Default)

### Pass 0 — Triage (5–10 minutes)

1) Identify the **one-sentence contribution** and confirm it with the user.
2) Extract the **top 3–7 claims** the paper relies on.
3) For each claim, note the current support:
   - empirical result (table/figure)
   - theorem/proof
   - citation / prior work
   - ablation / analysis
4) Flag immediate P0 risks (typical: missing baselines, unclear experimental protocol, unverified citations, paper “about X” but experiments test Y).

### Pass 1 — Section Review (primary deliverable)

Review sections in order (and check alignment between them):
1) Abstract
2) Introduction (motivation → gap → contribution bullets)
3) Related Work (positioning + not a bibliography dump)
4) Method (reproducible description + design justification)
5) Experiments / Results (fair baselines + full setup + statistical reporting)
6) Analysis / Ablations (claim-driven, not exploratory noise)
7) Limitations / Broader Impact / Ethics (venue-dependent)
8) Conclusion (tight restatement + constraints + future work without overclaim)

### Pass 2 — Consolidate into P0/P1/P2

Turn findings into an actionable issue list:
- P0 first (blockers / likely desk-reject causes)
- P1 next (acceptance probability movers)
- P2 last (polish)

### Pass 3 (Optional) — Revision Plan

If the user wants an execution plan, produce:
- 3–8 tasks with measurable acceptance criteria
- suggested order (dependency-aware)
- what can be done in parallel (writing vs experiments vs citations)

## Full-Parallel Workflow (Comprehensive)

When mode is `full-parallel`, do not collapse everything into one voice. Instead:

1) Run all tracks (A–G) as independent “mini-reviewers” and keep each track output visible.
2) Then produce the Final Synthesis:
   - View A: consolidated section-by-section review
   - View B: consolidated P0/P1/P2 issue list
   - minimal revision plan
   - conflicts & resolutions between tracks

Use:
- `references/full-parallel-protocol.md`
- `references/report-template.md`

## Rebuttal / Review Response Module

When reviews arrive, do:
1) Parse and classify each comment: **Major / Minor / Clarification / Missing baseline / Missing experiment / Writing / Citation / Misunderstanding**.
2) Choose a strategy per item: **Accept + change**, **Clarify**, **Defend**, **Add experiment**, **Defer (explain constraints)**.
3) Draft point-by-point responses with:
   - gratitude + precise restatement
   - what changed (or why not)
   - where to find it (section/figure/table)
   - evidence-based tone (no overpromising)

Use:
- `references/rebuttal-workflow.md`

## Citation Integrity Module (Hard Requirement)

Before submission, ensure:
- every non-trivial factual claim has a citation or empirical evidence
- every citation key resolves in the bibliography
- any newly added citations are verified (paper exists; BibTeX not fabricated)

If deep citation audit is requested, follow:
- `references/citation-integrity.md`
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