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nipreps/skills-comm

开发工具

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16 stars 质量 60 趋势 35Apache-2.0

Neuroimaging community skills repo - making LLMs leverage neuroimaging tools more effectively

概览

skills-comm gathers Agent Skills that teach LLM agents (Claude Code and other agents that read SKILL.md/AGENTS.md) how to drive real neuroimaging tools . Instead of letting an agent improvise commands for FSL, ANTs, FreeSurfer, DataLad, nipoppy, or a SLURM cluster, a skill encodes the operational knowledge — the right flags, the safe order of operations, the quality-control checks, and the reproducibility guardrails — so the work is repeatable across people and machines. The goal is : turn "how an expert actually runs this tool" into a package an agent can load on demand. - who want their software used the way it was meant to be used, even when an LLM is at the keyboard. - who want a coding agent that follows community best-practice (BIDS, YODA/DataLad provenance, explicit tool versioning) by default. - who want to share a reproducible recipe as a reusable skill. Each contribution lives under plugins/ as its own directory. A contribution is either a full (with a .

README

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skills-comm

A community collection of neuroimaging skills for LLM coding agents.

skills-comm gathers Agent Skills that teach LLM agents (Claude Code and other agents that read SKILL.md/AGENTS.md) how to drive real neuroimaging tools correctly and reproducibly. Instead of letting an agent improvise commands for FSL, ANTs, FreeSurfer, DataLad, nipoppy, or a SLURM cluster, a skill encodes the operational knowledge — the right flags, the safe order of operations, the quality-control checks, and the reproducibility guardrails — so the work is repeatable across people and machines.

The goal is operationalization: turn “how an expert actually runs this tool” into a package an agent can load on demand.

Who this is for

  • Method developers & tool authors who want their software used the way it was meant to be used, even when an LLM is at the keyboard.
  • Neuroimaging researchers who want a coding agent that follows community best-practice (BIDS, YODA/DataLad provenance, explicit tool versioning) by default.
  • Contributors who want to share a reproducible recipe as a reusable skill.

What’s in here

Each contribution lives under plugins/ as its own directory. A contribution is either a full Claude Code plugin (with a .claude-plugin/plugin.json manifest) or a bare skill collection (one or more SKILL.md directories). Current contributions:

Plugin What it operationalizes
plugins/datalad-cli DataLad / git-annex provenance and YODA-compliant analysis datasets
plugins/nipoppy-cli The nipoppy dataset-management lifecycle (curation → BIDS → process → extract)
plugins/brain-extraction Brain extraction (skull stripping) and its quality control
plugins/combat-harmonization ComBat-family harmonization strategy, execution, and QC
plugins/fc-matrix-generation Functional connectivity matrix generation from resting-state fMRI
plugins/job-monitor SLURM/PBS/LSF job monitoring and fast failure detection
plugins/pcntoolkit Give the AI agent knowledge for both the normative modelling scientific background and how it can be implemented in the pcntoolkit python package
plugins/registration Image registration and registration QC

skill-iterations/ is a teaching example: the same brain-extraction skill captured at six successive stages of refinement, showing how a raw draft is hardened into a reliable skill (fixing YAML, removing “Claude-isms”, generalizing across tools, improving QC). Read it to see what “good” looks like before you write your own.

Skill anatomy

在 GitHub 查看完整 README

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安装

npx skillfish add nipreps/skills-comm
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