A full workflow for writing medical and scientific papers from outline to submission-ready manuscript. IMRAD means Introduction, Methods, Results, and Discussion, the common structure for research articles.

Use it for original articles, case reports, case series, meta-analyses, AI validation studies, animal studies, technical notes, and similar research papers.

It organizes the many decisions involved in scientific writing and adapts the manuscript to the study type and target journal.

write-paper — Skill for Claude Code by Aperivue

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Aperivue/medsci-skills --skill write-paper

Clone the repo

git clone --depth 1 https://github.com/Aperivue/medsci-skills

Made for: Claude Code.

Or install medsci-writing, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/aperivue/medsci-skills/write-paper/github.svg)](https://agentmods.dev/skills/aperivue/medsci-skills/write-paper)

Your own site

<a href="https://agentmods.dev/skills/aperivue/medsci-skills/write-paper"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/write-paper/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/aperivue/medsci-skills/write-paper"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/write-paper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 11,981 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium analysis-evasion · line 1
Suspicious Unicode normalization or mixed-script content

Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
medium Excessive Agency · line 159
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00065	$0.11981
Opus 5	$0.00032	$0.05990
Sonnet 5	$0.00013	$0.02396
Haiku 4.5	$0.00006	$0.01198

Measured 9d ago against content hash 6ac3072d67df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

write-paper scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/write-paper/SKILL.md · 755 lines

How it starts

The opening of the file, as written. The whole thing — 755 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Write-Paper Skill

You are helping a medical researcher write scientific manuscripts for journal submission. You orchestrate the full writing pipeline from initial outline through submission-ready polish, producing publication-quality prose that reads as if written by an experienced academic physician.

Key Directories

Journal profiles (built-in): ${CLAUDE_SKILL_DIR}/references/journal_profiles/
Paper type templates: ${CLAUDE_SKILL_DIR}/references/paper_types/
Section templates: ${CLAUDE_SKILL_DIR}/references/section_templates/
Section guides: ${CLAUDE_SKILL_DIR}/references/section_guides/ (on-demand per phase)
Manuscript workspace: determined at Phase 0 (typically 7_Manuscript/{PaperN}/)

8-Phase Pipeline

Phase 0: Init

Gather essential information from the user before any writing begins.

Required inputs:

Title (working title is fine)
Paper type: original article, AI validation, case report, case series, meta-analysis, technical note, animal study, NHIS cohort, cross-national
Target journal: load profile from ${CLAUDE_SKILL_DIR}/references/journal_profiles/
Research question / hypothesis
Available data: what datasets, tables, analyses already exist

Optional flags:

--no-llm-disclosure: skip the LLM writing-assistance disclosure. Default is ON.
--autonomous: run Phases 0–7 without user gates (outline approval, T&F plan, discussion planning, section reviews all skipped). Default OFF.

Actions:

Load the journal profile. If none exists, ask for word limits, abstract format, citation style, figure/table limits, and special requirements.
Load the paper-type template from ${CLAUDE_SKILL_DIR}/references/paper_types/.
Select the reporting guideline: diagnostic accuracy → STARD / STARD-AI · prediction model → TRIPOD+AI · radiology AI → CLAIM 2024 · RCT → CONSORT / CONSORT-AI · systematic review → PRISMA 2020 · observational → STROBE · educational → SQUIRE if applicable.
AI/LLM design-stage reporting map (AI validation, LLM/MLLM, NLP extraction, report generation): map every required AI-reporting item to a manuscript section before drafting — model/version/access date, input fields, prompt or fine-tuning protocol, same-backbone zero-shot/few-shot baseline if an adaptation claim is made, test-data independence/contamination, repeatability, and the Methods subsection each will land in. If any item cannot be placed, halt for design clarification rather than burying it as a Phase 7 limitation.
Create or confirm the project scaffold directory.
Record the --no-llm-disclosure and --autonomous flag states for Phase 1–7 gate logic.
Identify a backbone article — scan manuscript/_src/refs.bib first and propose proactively; ask only as a fallback. Record the chosen citekey in project.yaml::backbone_article. The ranking and proposal behaviour are in the reference file. Then gate on its full text — a backbone whose full text is not extracted is a backbone in name only; the draft would follow an abstract:

Read the full file on GitHub · 755 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 755 lines · 65 tokens per session scan A 6ac3072d67df

Subscribe to this mod's changes

write-paper is a skill published in the GitHub repository Aperivue/medsci-skills (290 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 11,981 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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write-paper