research-skills

Research Skills

A collection of Claude Code skills for academic research workflows.

Skills

Slides from a paper? Two different tools, on purpose. Use scholar-slides for a faithful, editable live talk — equations, numbers, tables, and citations stay exact and projector-ready. Use paper-slide-deck for stylized visual images to read or share, where look-and-feel matters more than editable precision (its slides are AI-generated images, so math and data are not editable and can be garbled — don't use it for a defense or a results-heavy talk).

Doing a review? Two stages, two skills. lit-search builds the corpus — it finds the papers and proves how complete the search was. medical-imaging-review writes the review from papers you already have. Running a systematic review end to end means lit-search first, then medical-imaging-review over its dois.md.

Installation

Copy the desired skill folder into your Claude Code skills directory:

cp -r medical-imaging-review ~/.claude/skills/
cp -r paper-slide-deck       ~/.claude/skills/
cp -r research-proposal      ~/.claude/skills/
cp -r scholar-slides         ~/.claude/skills/
cp -r lit-search             ~/.claude/skills/

scholar-slides and lit-search carry their own toolchains; after copying, provision them once:

cd ~/.claude/skills/scholar-slides && ./install.sh
cd ~/.claude/skills/lit-search     && ./install.sh   # needs uv + Python 3.11+

Medical Imaging Review Skill

A systematic workflow for writing survey papers, systematic reviews, and literature analyses on medical imaging AI topics.

Features

• Structured 8-phase write-with-verify workflow (review-type routing → paradigm capture → init → collect-and-verify → outline/taxonomy → per-claim-verified writing → peer review → submission prep)
• Review-type routing — narrative / method survey / scoping / systematic, with matching reporting standards (PRISMA 2020, QUADAS-3, CLAIM 2024, TRIPOD+AI)
• Citation integrity as a hard gate — every [N] verified for existence, author, number, and direction before commit; an executable audit script (scripts/audit_manuscript.py) locked by a fixture test suite
• Evidence-calibrated writing voice — match claim strength to evidence; the default-hedging register is explicitly removed as an AI tell
• Domain-specific 3-axis method taxonomy across multiple medical imaging domains
• Quality checklists and Zotero-first literature collection with tool-portable fallbacks

Supported Domains

• Coronary Artery Analysis (CCTA)
• Lung Imaging (CT/X-ray)
• Brain Imaging (MRI/CT)
• Cardiac Imaging (MRI/CT/Echo)
• Pathology (Whole Slide Images)
• Retinal Imaging (Fundus/OCT)

Files

Paper Slide Deck Skill

Transform any content into stylized, shareable slide images (AI-generated), with figure detection and high-resolution page rendering from PDFs.

Text, math, and data are baked into each image and not editable — for a faithful, editable academic talk (组会/答辩/results-heavy) use scholar-slides instead.

Features

• Caption-based figure detection from PDF papers (locates the page; human confirmation recommended for dense two-column layouts)
• Figure-to-slide mapping with full-page high-res render + template container (not per-figure bbox cropping)
• 17 visual styles (academic-paper, sketch-notes, minimal, etc.)
• Gemini API integration (gemini-3-pro-image) for AI slide generation, with a post-generation garbled-text proofread pass
• PPTX/PDF export with merge scripts

Workflow

1. Analyze paper and detect figures/tables
2. Generate outline with auto IMAGE_SOURCE mapping
3. Extract figures from PDF (or AI-generate)
4. Apply academic templates
5. Merge to PPTX/PDF

Files

Scripts

Research Proposal Skill

Generate high-quality academic research proposals — PhD applications, research plans, 研究计划书 / 开题报告 — following Nature Reviews-style academic writing conventions.

Features

• Structured 5-phase workflow with a write-with-verify content stage: Requirements → Literature (+verification gate) → Outline (approval red line) → Content (section-by-section) → Output
• Citation-integrity guardrails: every reference verified to exist (DOI/PMID/arXiv or Zotero) with author and year matching the source — unverifiable entries are flagged, never fabricated
• Multi-source literature integration: WebSearch, Zotero MCP, arXiv, PubMed (with tool-portable fallbacks)
• Bilingual support: English and Chinese (中文)
• Domain adaptation: STEM (incl. computational / ML / AI-for-Science), Humanities, Social Sciences
• Academic writing style: prose-based, evidence-calibrated language; reference count follows the argument (no padding quota)

Workflow

1. Gather requirements (topic, domain, language, word count)
2. Collect literature from multiple sources
3. Generate outline for user approval
4. Write full proposal based on approved outline
5. Output Markdown with quality checklist

Files

Output

• Target: 2,000-4,000 words (default ~3,000)
• References: count follows the argument (typically 25–50; no minimum, no padding), each verified
• 3-5 figure suggestions
• Markdown format (convertible to DOCX/PDF via pandoc)

Scholar Slides Skill

Turn a research paper (or arXiv/DOI link, or a topic) into a fidelity-first slide deck — one where every equation, table, number, figure, and citation stays true vector/text and traceable to the source, never rasterized by an image model and never fabricated. Where paper-slide-deck optimizes visual style via text-to-image, scholar-slides inverts the priority for scholarly work: source fidelity > polish, behind an executable integrity gate.

Features

• Fidelity-first rendering — KaTeX vector equations, real ``/OOXML tables, cited figure crops; numbers grounded against the source, no fabrication
• Integrity QA gate — number grounding, [MISSING]/[UNVERIFIED] flags instead of silent fills, PPTX-parity regression, a scoreable aesthetics rubric
• Two registers — journal-club (组会, reading-first) and conference (big-room), via a token-based theme system
• Bilingual — English default, full 中文 / CJK support
• Zotero-first citations with Crossref / arXiv / DOI fallback

Outputs

• Interactive reveal.js deck (with browser speaker view)
• One-page-per-slide vector PDF
• Editable PPTX (native text, bullets, tables, speaker notes; equations/figures as flagged images)
• Speaker notes with a bilingual talk-time estimate

Install & run

cd ~/.claude/skills/scholar-slides && ./install.sh   # .venv + npm + Chromium, then self-checks

Prereqs: Python 3.11+, Node 18+. For Chinese decks on Linux: sudo apt-get install fonts-noto-cjk (macOS/Windows already have CJK fonts).

Known limitation

Figure localization is layout-dependent — ~95–100% on single-column / arXiv / Nature-style papers, ~75% on dense IEEE/TPAMI two-column pages. Low-confidence crops are flagged for you to confirm, never silently wrong. Stress-tested over 9 cross-layout papers: 0 crashes, 98% of figures localized. See scholar-slides/README.md for the full story.

Lit Search Skill

Retrieve everything published on a topic inside a time window, and be able to say how much you missed. Chat-style search returns "the top few by relevance" — not reproducible, and silent about its own gaps. This skill turns retrieval into a deterministic pipeline: multi-source × full pagination × citation closure × a measurable saturation criterion, then delivers the corpus.

Features

• Recall is measured, not claimed — gold-set recall, out-of-window leakage controls, per-source unique contribution, snowball saturation curve, PRISMA counts that refuse to render when they don't add up
• Says what it did NOT do — sources declared but never contacted, unimplemented sources, skipped citation closure: each appears in coverage_report.md with a computed reason. "No gaps" is written out as a conclusion, never implied by a blank section
• Annotates quality, never filters — CCF grade / journal metric / citation percentile decide order, not inclusion. A threshold would conflate "not evaluated" with "low quality" (measured: cutting at 4.0 dropped 340 papers that had no metric at all)
• Reaches closed publishers' metadata — Elsevier 95.6% / Springer 80.4% / IEEE 98.7% abstract coverage via OpenAlex + PubMed. It does not bypass paywalls
• **Human adjudication flows