mckinsey-style-visuali…
A skill for Claude Code that turns notes, metrics, and prose into clean, professional visuals such as board slides, charts, process flows, and timelines. It outputs SVG slides, an animated HTML deck, or a design spec.
A Claude Code skill for medical and scientific researchers that guides a manuscript through the full pipeline, from literature search and stage-gated IMRAD drafting to adversarial review and submission and revision loops.
Claude Code
$ npx -y skills add kgraph57/paper-writer-skill --agent claude-code
Codex
$ npx skills add kgraph57/paper-writer-skill -a codex
Cursor
$ npx skills add kgraph57/paper-writer-skill -a cursor
Gemini CLI
$ npx skills add kgraph57/paper-writer-skill -a gemini-cli
GitHub Copilot
$ npx skills add kgraph57/paper-writer-skill -a github-copilot
OpenCode
$ npx skills add kgraph57/paper-writer-skill -a opencode
Windsurf
$ npx skills add kgraph57/paper-writer-skill -a windsurf
Not a manuscript factory. A research engine.
A Claude Code / agent skill for medical and scientific manuscripts: Discovery gates, stage-gated IMRAD drafting, EN+JP humanizing, adversarial review, and submission/revision loops. Humans stay sovereign on the 💡 IDEA and the 📊 DATA.
English | 日本語
Live intro: https://kgraph57.github.io/paper-writer-skill/
references/humanizer-academic.md.table1.py, SR helpers, compile/word-count scripts — CI runs unittest + shell syntax checks.# 1. Install as an agent skill (Claude Code, Cursor, Codex, and other skills hosts)
npx skills add kgraph57/paper-writer-skill
Or clone into Claude Code’s skills directory:
git clone https://github.com/kgraph57/paper-writer-skill.git ~/.claude/skills/paper-writer
Then ask in plain language:
Use the paper-writer skill to start a CARE case report from these de-identified notes…
論文を書く。症例報告。CARE。データは匿名化済み。
Triggers: write paper / start manuscript / research paper / 論文を書く / 論文執筆 / 原稿作成 — or /paper-writer in Claude Code.
graph LR
P0["−1. Discovery\n(question · novelty · design · pre-reg)"] --> P1[1. Literature Search]
P1 --> P2[2. Outline]
P2 --> P25[2.5 Tables/Figures]
P25 --> P3[3. Draft]
P3 --> P4[4. Humanize]
P4 --> P5[5. References]
P5 --> P6[6. Quality Review]
P6 --> P65["6.5 Adversarial Review"]
P65 --> P7[7. Pre-Submission]
P65 -.->|KILL| P0
P7 --> P8["8. Revision"]
P8 --> P9["9. Post-Acceptance"]
P7 -.-> P10["10. Rejection → Resubmit"]
P10 -.-> P1
Optional Python packages for analysis/PDF utilities: python -m pip install -r requirements.txt. Literature work uses WebSearch/WebFetch and public literature APIs — not a zero-network skill (by design).
Discovery → draft → humanize → adversarial catch — an illustrative CARE spark (PHI-free) showing why gates beat “just write the abstract.”
| Type | Structure | Reporting Guideline |
|---|---|---|
| Original Article | Full IMRAD | STROBE / CONSORT |
| Case Report | Intro / Case / Discussion | CARE |
| Review Article | Thematic sections | — |
| Systematic Review | PRISMA-compliant | PRISMA 2020 |
| Letter / Short Communication | Condensed IMRAD | Same as original |
| Study Protocol | SPIRIT-compliant | SPIRIT 2025 |
Every phase is guarded by a quality gate. If the gate returns FAIL, the system generates structured feedback, dispatches a fixer agent in revision_mode, and re-checks — up to 3 iterations before escalating to the user.
Literature (≥10 papers, valid DOIs) → Outline (IMRAD + citations mapped) → Tables/Figures → Section draft score → Humanize (high-priority AI patterns = 0) → References (no fabrication / orphans) → Cross-section consistency → Submission package.
| Agent | Role |
|---|---|
paper-lit-searcher | Database-specific literature search |
paper-table-figure-planner | Table and figure design |
paper-section-drafter | Section drafting |
paper-humanizer | AI writing pattern removal |
paper-ref-builder | Citation collection and verification |
paper-section-reviewer | Per-section quality check |
paper-quality-gate | Cross-section consistency + final verdict |
| Path | What |
|---|---|
SKILL.md | Main workflow definition |
docs/ | GitHub Pages landing |
examples/case-studies/ | Public case study |
templates/ | Section / project / CARE / SR templates |
references/ | Humanizer, adversarial, guidelines, journals… |
scripts/ | Compile, word-count, table1, SR utilities |
LAUNCH.md | Posting kit (X JP/EN, Show HN) |
SECURITY.md | PHI / network / permissions |
Full file tree and phase tables remain in SKILL.md and the templates/references trees (37 templates · 30 reference docs · 8 scripts).
| Language | Coverage |
|---|---|
| English | All templates and guides, 18 AI writing detection patterns |
| Japanese | Bilingual templates, 13 AI writing detection patterns, である-style |
SKILL.mdpython -m pip install -r requirements.txt for analysis/PDF helperspython -m py_compile scripts/*.py
bash -n scripts/*.sh
python -m unittest discover -s tests -v
MIT — Copyright (c) 2026 KEN.
See CHANGELOG.md for details.
If you want manuscripts that survive review — and refuse to lie about data — ★ Star the repo and install it on your agent.
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A Claude Code skill for medical and scientific researchers that guides a manuscript through the full pipeline, from literature search and stage-gated IMRAD drafting to adversarial review and submission and revision loops. Install it with the command on its page. It includes paper-writer-skill. Its skills do not fire on their own yet. Free and open source.
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