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@ai4s-research/ai4s-skills

Agent skills for AI-for-Science research workflows

This repo packages seven skills that guide an agent through research exploration, literature surveying, experiment setup, paper writing, and integrity checks. The skills are meant to be installed into a project or global skills folder, then invoked from Claude Code, Cursor, Codex, or another coding agent.

222 stars21 forksPythonUpdated 1mo ago
Who it's for

Builders who want their agent to turn a research direction into surveys, runnable experiments, and paper drafts with traceable sources.

What it delivers

You can move from a broad idea to a cited survey, experiment package, and paper draft with less re-explaining and more repeatable work.

What it does

Research explorer

Explores a broad topic and produces `research_exploration.md`, `topic_matrix.md`, and `literature_pre_survey.md`.

Literature survey

Writes a survey with real citations, LaTeX source, and topic figures, aiming for a publication-style PDF.

Experiment suite

Builds a runnable experiment package with design notes, code, `results.json` provenance, figures, and a report.

Paper writer

Assembles a paper from prior survey and experiment outputs, with figures, tables, citations, and a final PDF.

Mindmap render

Turns a `topic_matrix.md` file into a rendered mindmap image using the included Python script.

Integrity auditor

Checks a paper for image, numerical, and logical issues and writes an `audit_report.md` with evidence grading.

Shared workflow path

Passes work between skills through `output/<skill>/<slug>/latest/` so later steps can reuse earlier outputs.

Validation script

Uses `tools/validate_skills.py` to check skill structure and frontmatter in CI.

How to get it

  1. 1Run the installer from the project you want the skills in
    git clone https://github.com/ai4s-research/ai4s-skills
    
    cd /path/to/your-project
    /path/to/ai4s-skills/install.sh                              # all skills → ./.claude/skills
    /path/to/ai4s-skills/install.sh paper-writer                 # or specific ones
    SKILLS_DIR=~/.claude/skills /path/to/ai4s-skills/install.sh  # global instead
  2. 2With Cursor, Codex, or Aider, point the agent at the skill file
    Read skills/literature-survey/SKILL.md and its references/, then produce the survey
    for "<your topic>" as specified.

README

AI4S Skills — agent skills for AI for Science

Seven agent skills for AI-for-Science research — turn a research direction into literature surveys, runnable experiments, publication-grade papers, and integrity audits, with every citation, number, and figure traceable to its source.

English · 中文

License: MIT DOI 7 skills PRs Welcome linux.do


Contents

The skills

SkillRolePrimary output
ai4s-agentRuns the four skills below in orderthe full package
research-explorerExplore topics from a broad directionresearch_exploration.md, topic_matrix.md, literature_pre_survey.md
literature-surveyWrite a literature survey6–20 pp PDF, 60+ real citations, LaTeX source, topic-specific figures
experiment-suiteBuild an experiment packagedesign doc, runnable code, results.json with provenance, figures, report
paper-writerWrite a research paper8–14 pp PDF, 200+ citations, 4–8 figures, tables
mindmap-renderRender a mindmapimage from a topic_matrix.md (Python script)
integrity-auditorAudit a paper's integrityimage / numerical / logical findings, 4-level evidence grading, audit_report.md

Each skill is a folder with a SKILL.md plus its own references, templates, and tools. MIT-licensed; works with Claude Code, Cursor, Codex, and Aider.

How they connect

direction
   │
   ▼
[1] research-explorer ──▶ pick one $TOPIC
   │
   ├──▶ [2] literature-survey   → survey PDF + bibliography.bib
   ├──▶ [3] experiment-suite    → results.json + figures/
   └──▶ [4] paper-writer        → paper PDF  (reuses [2] and [3])

integrity-auditor ──▶ audits any paper: external PDF / DOI / arXiv, or [4]'s output

ai4s-agent runs steps 1–4 in order. Skills pass work to each other through a shared slug and the path output/<skill>/<slug>/latest/.

Authenticity

The focus of the project. Every skill enforces:

PrincipleIn practice
Real citationsEvery BibTeX entry links to a URL the agent fetched in the same session; none from memory.
Labelled numbersEvery number is marked measured, simulated, or illustrative; simulated values are never reported as measured.
Runnable experimentsexperiment-suite outputs runnable code and a results.json with provenance. Supply real results and they replace the simulated ones; the "simulated" disclosure is then removed.
Resumable runsLong tasks save progress after each step and continue from the last checkpoint, so a reported "done" reflects completed work.
Publication layoutReadable booktabs tables; final-size raster QA; vector-PDF figures with embedded fonts, shared color-safe styling, and no generic diagram-tool output.
Review disclosureEvery generated document states that domain-expert review is recommended.
Integrity checksintegrity-auditor inspects a paper for image, numerical, and logical problems and grades the evidence.

Example

A complete run from experiment-suite + paper-writer: "Learning the Burgers Solution Operator with a Fourier Neural Operator" — an 8-page paper backed by code the agent wrote and ran. Full artifact in examples/fno-burgers/ (paper, code, results.json, report).

paper page 1paper page 2paper page 3
paper page 4paper page 5paper page 6
The 8-page paper (first 6 pages) — click any page for the full PDF.
  • Real code, really runmodel.py is a 1-D FNO; the full study runs in ~35 min on a laptop CPU.
  • Measured results — FNO 4.41% rel-L2 vs MLP 21.63% and CNN 67.69% (3 seeds); zero-shot super-resolution holds 4.2–4.7% from grid 128 to 1024.
  • Real citations — 22 references, each traceable to its source.

Every number is measured (provenance in results.json); the paper states it was AI-generated and recommends domain-expert review.

Install

Run the installer from the project you want the skills in:

git clone https://github.com/ai4s-research/ai4s-skills

cd /path/to/your-project
/path/to/ai4s-skills/install.sh                              # all skills → ./.claude/skills
/path/to/ai4s-skills/install.sh paper-writer                 # or specific ones
SKILLS_DIR=~/.claude/skills /path/to/ai4s-skills/install.sh  # global instead

To install by hand, copy any skills/<name>/ into ~/.claude/skills/ (global) or <project>/.claude/skills/ (project).

Usage

In Claude Code:

Use the literature-survey skill to write a survey on <your topic>.

With Cursor, Codex, or Aider, point the agent at the skill file:

Read skills/literature-survey/SKILL.md and its references/, then produce the survey
for "<your topic>" as specified.

Each SKILL.md directs the agent to read its references/ first; those files hold the procedures for bibliography expansion, figures, layout, and quality checks.

Repository layout

ai4s-skills/
├── skills/
│   ├── ai4s-agent/          SKILL.md + references/
│   ├── research-explorer/   SKILL.md
│   ├── literature-survey/   SKILL.md + references/ + templates/survey/
│   ├── experiment-suite/    SKILL.md + references/ + figure_examples/
│   ├── paper-writer/        SKILL.md + references/ + templates/paper/
│   ├── mindmap-render/      SKILL.md + scripts/ + tests/
│   └── integrity-auditor/   SKILL.md + references/ + forensics_tools/ + templates/ + tests/
├── tools/validate_skills.py   structure / frontmatter validator (run in CI)
├── install.sh
└── .github/workflows/ci.yml

Each SKILL.md carries YAML frontmatter (name, description) so an agent can find and route to it.

Included tools

Small, single-purpose scripts the skills call. Each directory has its own requirements.txt.

  • skills/integrity-auditor/forensics_tools/ — image duplication / ORB matching, panel splitting, channel checks, magnitude (Benford-style) consistency, decimal matching, spreadsheet aggregate consistency.
  • skills/experiment-suite/figure_examples/ — a matplotlib style kit (style_kit.py) and worked figure examples.
  • skills/mindmap-render/scripts/generate_mindmap.py.

Contributing

A new skill needs:

  1. skills/<name>/SKILL.md with name and description frontmatter (name = folder name).
  2. Optional references/, templates/, and tools.
  3. No import anthropic / import openai.
  4. python tools/validate_skills.py passing (CI runs it on every PR).

See CONTRIBUTING.md and the Code of Conduct.

Citation

If you use AI4S Skills in your research, please cite it:

@software{ai4s_skills,
  author  = {{The AI4S Skills Contributors}},
  title   = {AI4S Skills: open-source agent skills for AI for Science},
  year    = {2026},
  version = {0.1.0},
  doi     = {10.5281/zenodo.21297455},
  url     = {https://github.com/ai4s-research/ai4s-skills},
  license = {MIT}
}

The DOI above cites all versions; GitHub's "Cite this repository" button (generated from CITATION.cff) provides the same reference in APA and BibTeX.

License

MIT.

Outputs are drafts. Review by a domain expert is recommended before any citation, submission, or decision. Verify numbers, citations, and claims.

Acknowledgments

Thanks to linux.do — a vibrant tech community where this project is shared and discussed.

Files in the repo

Repository payload14 top-level entries
  • .github
  • assets
  • examples
  • skills
  • tools
  • .gitignore
  • CITATION.cff
  • CODE_OF_CONDUCT.md
  • CONTRIBUTING.md
  • install.sh
  • LICENSE
  • PROGRESS.md
  • README.md
  • README.zh.md

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