/paper-writer-skill

name: paper-writer
description: "Medical/scientific paper writing workflow skill. Manages the full pipeline from literature search to submission-ready manuscript. Creates and manages a project directory with IMRAD-format section files, literature matrix, reference management, and quality checklists. Supports both English and Japanese papers. Triggers: 'write paper', 'paper-write', 'start manuscript', '論文を書く', '論文執筆', '論文プロジェクト', 'manuscript', 'research paper', '原稿作成'."
context: fork

Paper Writer Skill

Full-pipeline academic paper writing assistant. From literature search to submission-ready manuscript.

Overview

This skill manages the entire paper writing workflow:

[Discovery] → Literature Search → Outline → Tables/Figures → Draft → Humanize → References → Quality Review → [Adversarial Review] → Pre-Submission → [Revision] → [Post-Acceptance] → [Rejection → Resubmission]

Each paper is a **project directory** containing structured Markdown files for every section, a literature matrix, and quality checklists.

AI-for-Science Operating Model

This skill is not only a *manuscript factory* (write → format → submit). It is a *research engine* that wraps the writing pipeline in a discovery loop and names the two things only a human can supply. **Before doing anything else, read `~/.claude/skills/paper-writer/references/ai-for-science-model.md`** — it defines:

• **The two human-sovereign inputs.** 💡 **IDEA** (what is worth asking, what it

means, what is ethical) and 📊 **DATA** (real, IRB-approved, never machine-originated). AI proposes and executes everything else at full power; the human owns exactly these two gates. AI must never originate a data point, participant, or result.

• **The loop.** Phase −1 Discovery (hypothesis → novelty → design → pre-registration

lock) feeds the existing pipeline; Phase 6.5 Adversarial Review red-teams the central claim before any journal sees it. A red-team KILL sends the project back to Discovery — that is the system working.

• **The three integrity guardrails** that make AI-accelerated research *more*

rigorous, not less: **pre-registration** (anti-HARKing), **novelty check** (anti-reinvention/inflation), **adversarial self-review** (anti-slop). Each prevents a documented frontier failure mode.

• **The autonomy dial** (Manual / Co-pilot / Autopilot). Hard rule for clinical

work: the 💡 IDEA gate, the 📊 DATA gate, and the pre-registration lock are **never** autopilot.

The rest of this document is the execution detail. When a phase touches a sovereign gate, stop and get the human; everywhere else, run at full power.

Supported Paper Types

| Type | Structure | Reporting Guideline | Notes | |------|-----------|-------------------|-------| | **Original Article** | Full IMRAD | STROBE / CONSORT | Default | | **Case Report** | Intro / Case / Discussion | CARE | Separate templates | | **Review Article** | Thematic sections | - | Flexible structure | | **Letter / Short Communication** | Condensed IMRAD | Same as original | Word limit focus | | **Systematic Review** | PRISMA-compliant | PRISMA 2020 | With PRISMA checklist | | **Study Protocol** | SPIRIT-compliant | SPIRIT 2025 | For trial registration papers |

Workflow

Phase −1: Discovery (the research engine)

**This phase is what separates a research engine from a manuscript factory.** The rest of the skill assumes the research question and the data already exist. Phase −1 produces them — a novelty-checked, powered, pre-registered study plan — *before* Project Init. Read `~/.claude/skills/paper-writer/references/ai-for-science-model.md` first for the operating model.

**Phase −1 is re-enterable — enter at the first guardrail not yet passed.** It is not all-or-nothing: a study that already has a sharpened question (but no novelty check, power, or pre-registration) enters *mid-chain*, not at the forge. Route by the **Phase −1 entry matrix**:

| What the user arrives with | Enter at | How | |---|---|---| | **(a)** A raw clinical observation | **−1.1 Forge** | Run `templates/research-question.md` in **Mode A** (forge a question from the spark), then continue −1.2 → −1.3 → −1.4 in order. | | **(b)** An existing question / advanced protocol, **pre-data** | **−1.2 Novelty** | Run `templates/research-question.md` in **Mode B** (resume/refine — back-fill PECO, single Attack pass, FINER) first, then **−1.2 novelty**, then **−1.3 design as an AUDIT of the existing protocol** (not a fresh draft — check it against `templates/study-design.md`, fix gaps), then **−1.4 prereg**, then **run `references/adversarial-review.md` in design-stage mode (§0, pre-data) BEFORE the pre-registration lock** so cheap design fixes land before freezing. | | **(c)** Question + design + data all locked | **Skip to Phase 0** | Pure writing-up. Still confirm the 💡 IDEA and 📊 DATA gates are human-owned and that a pre-registration exists or is consciously waived (and disclosed as such). |

**−1.2 novelty is the mandatory minimum entry for any unpublished study** — novelty cannot be assumed from the fact that a protocol is already being written. Only path (c) (already locked + data in hand) may skip it.

Start the project's accountability ledger now: create `log/human-loop-ledger.md` from `~/.claude/skills/paper-writer/templates/human-loop-ledger.md` and declare the autonomy mode (Manual / Co-pilot / Autopilot). Record every gate decision in it from here on.

Step −1.1: Forge the research question (💡 IDEA gate)

Read `~/.claude/skills/paper-writer/templates/research-question.md`. From the user's clinical observation, generate 5–15 candidate questions, debate and rank them by FINER, evolve the top 2–3 — then **stop and have the human select**. AI never auto-selects the question. Output: one sharpened research question with its PICO.

Step −1.2: Novelty check (guardrail: anti-reinvention)

Read `~/.claude/skills/paper-writer/references/novelty-check.md`. Run a live-literature