IcyCreamDAS/shidi-skill

Research workflow skill for AI coding agents: literature review · experiment design · scientific figures · paper reading · data organization

You bring the ideas, shidi does the legwork.

中文 | English

shidi ("junior lab mate" in Chinese) is a complete research workflow that lives inside your AI IDE — not a prompt template. Hand it an idea (literature research / experiment design / figures / paper reading / data chores), and it returns real deliverable files. Your data stays local. No platform or model lock-in.

It's not fire-and-forget, either — shidi is meant to be bossed around while you do something else. Say "shidi, help me with …", and it asks when it must, runs the rest, and hands you the files.

Built for AI for Science workflows, grad students and researchers using agentic AI — literature review, experiment design, figures and paper reading become deliverable, cross-verifiable files instead of chat answers.

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👀 Demo

Screenshots below are illustrative (content redacted) — real runs produce fresh files for your own topic.

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✨ What's New

• 2026-08 — 📥 Batch PDF download (OpenAlex/Unpaywall OA lookup; failures classified and reported, never silently skipped)
• 2026-08 — 📄 Multi-format reports (Markdown → HTML → PDF via headless Edge printing, zero deps)
• 2026-08 — 🔍 PDF extraction layer (text-based → Markdown to save context; scans auto-tagged needs_vision for the vision route)
• 2026-08 — 🗂 Per-angle intermediate reports (parallel multi-agent research: one file per angle, merge by reading files only — main context never overflows)

📤 Deliverables

Every job ends in real files — not chat text.

Every delivery looks like this. Take the brief to another LLM for independent verification — every comment gets an adopt/reject + reason, loop until you're satisfied.

✨ Why shidi

Chatting with a raw model	shidi
Answers live in the chat log	Delivers files: reports, briefs, figures, CSVs — archivable, citable, shareable
You nudge it step by step	Built-in workflow (search → score → read → report → verify); answer 3 parameters and it runs
Hallucinations on your conscience	Six-dim scoring, DOI triple-dedup, no-fabrication rule, honest reading-depth labels, mandatory verification brief
Behavior changes with the model	Pure SKILL.md + Markdown — works in Claude Code / Codex / OpenClaw / any SKILL.md agent

🚀 Capabilities

Capability	Description
📚 Literature research	3 parameters up front → 3×3=9 angles → top-journal targeted search + fallback chain → six-dim scoring → graded reading → batch PDF download → file report
🧪 Experiment design	Free-form approach brainstorm → literature-backed → principle / steps / precautions / unvarnished flaw list
📈 Figures	CSV/TXT/Excel → clean → compute (numpy/scipy/sympy) → publication-grade rendering, with Origin-ready data export
🔬 Paper reading	source-map six-step deep read → 16-section paper cards → glossary
🔄 Cross-verification (the soul)	Always emits a verification brief → another LLM checks independently → iterate in loops
📋 Lab notes	Standardized experiment/batch IDs, YAML frontmatter archiving

🧭 Flow

flowchart TD
    A["Decide topics"] --> B["Research"]
    B --> C["3 parameters<br/>{count, domain, requirements}"]
    C --> D["Search (T1→T2→T3)"]
    D --> H["Merge & score"]
    H --> E["Read (✅/⚠/❌)"]

    E -->|out| F["Lit summary ①"]
    E -->|out| G["References ②③<br/>PDF or DOI+GB/T 7714"]

    F --> I{"More full-texts?"}
    G --> I

    I -->|yes| J["User uploads PDF"]
    J -->|supplement| H

    I -->|no| K["Final report"]
    I -->|no| L["Verify brief (always)"]
    K --> M{"Cross-verify?"}
    L --> M

    M -->|yes| N["Another LLM checks"]
    N -->|revise| D

    M -->|no| O["Done ✓"]

🚀 Quick Start

git clone https://github.com/IcyCreamDAS/shidi-skill.git
cp -r shidi-skill/skills/shidi ~/.claude/skills/

Then just say:

shidi, research the literature on XX — 20 papers
shidi, design an experiment for XX
shidi, plot this data
shidi, read this paper in depth for me

Just "shidi" works too — it confirms the task type before starting. Compatible with any agent that follows the SKILL.md spec (Claude Code / Codex / OpenClaw / OpenCode…).

[!IMPORTANT]

An executor, not a genie

harness + model = agent — shidi owns the workflow, the model sets the ceiling. And it never decides for you: angle selection, parameters, trade-offs all bounce back to you. It takes the grunt work; the ideas and judgment stay yours.

🤖 Persona

• Calls you "senior" (or "senior sister" if you say so)
• A humble, slightly cheeky junior: "here's what I made, what do you think?"
• Praises you when corrected ("good catch, senior"), never bends on science
• Persona activates only on the trigger word — other conversations unaffected

Yes, it asks a lot of questions — that's how you know it's really shidi.

⚙️ Dependencies

• Zero external deps: pure SKILL.md + Markdown, nothing to install
• Optional: numpy/scipy/matplotlib/pandas/sympy (figures; pyvista for 3D), pdf-inspector (PDF extraction layer)
• Search fallback chain: WebSearch → open scholarly APIs (OpenAlex/Crossref/arXiv, no keys needed)

🛡 Guardrails

1. Capped six-dim scoring, totals recomputed
2. Topic-match <10 → veto
3. DOI / arXiv ID / URL triple dedup
4. No fabrication — unverifiable claims are labeled "unverified"
5. Honest reading-depth labels: full text ✅ / abstract ⚠ / unavailable ❌
6. Every verification comment gets adopt/reject + reason — never blind agreement

📜 Credits

Design ideas borrowed from nature-skills (Yuan1z0825 team): routing, six-dim scoring, search fallback chain, paper cards.

📄 License

MIT License — free to use; just buy shidi a bubble tea 🧋