bigbio/sdrf-skills
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Agentic plugins to annotate SDRF using Claude; Codex; Cursor; Gemini
概要
Structured skills that give AI assistants expert-level capabilities for annotating, validating, improving, and reviewing proteomics metadata in the SDRF format. Instead of guessing at ontology terms or SDRF rules, the agent follows the methodology of experienced annotators using real tools (OLS, PRIDE, PubMed). The specification data (column definitions, templates) lives in a git submodule and is read at runtime, so the skills stay current as the spec evolves. Four skills. Three are slash commands under /sdrf-skills:; sdrf-adversarial-review is dispatched by sdrf-annotate into a fresh context and is never typed as a command (a pipeline can also run it directly as a separate task): Then pip install -e . from the checkout gives you the sdrf-tools command (pip install -e '.[mcp]' adds the bundled MCP server's dependencies), and sdrf-tools doctor checks parse_sdrf, sdrf-tools, the spec submodule and techsdrf, and says what to install for anything missing.
README
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sdrf-skills
Turn Claude Code, Cursor, OpenAI Codex, Gemini CLI, or OpenCode into an expert proteomics SDRF annotator.
Pick a dataset → the agent fetches PRIDE + paper → you review a validated SDRF.
Structured skills that give AI assistants expert-level capabilities for annotating, validating, improving, and reviewing proteomics metadata in the SDRF format. Instead of guessing at ontology terms or SDRF rules, the agent follows the methodology of experienced annotators using real tools (OLS, PRIDE, PubMed). The specification data (column definitions, templates) lives in a git submodule and is read at runtime, so the skills stay current as the spec evolves.
Available skills
Four skills. Three are slash commands under /sdrf-skills:; sdrf-adversarial-review is dispatched by
sdrf-annotate into a fresh context and is never typed as a command (a pipeline can also run it
directly as a separate task):
| Skill | What it does |
|---|---|
/sdrf-skills:sdrf-annotate |
Everything about one SDRF. A PXD: record + paper → samples.tsv + technical.tsv → sdrf-tools build → validate → independent review, always. An existing .sdrf.tsv: review it (validate, structure, check, reconcile, cross-reference, score, then the independent review). A question: explain the format, look up a term, or plan what to capture. A short core plus references/ it reads only when a step needs them |
/sdrf-skills:sdrf-contribute |
Contribute a reviewed SDRF back to sdrf-annotated-datasets via PR, behind the review gate |
/sdrf-skills:sdrf-campaign |
Screen a class of studies against your criteria into a resumable TSV, then loop sdrf-annotate over the included ones, keeping only evidence-backed improvements |
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インストール
npx skillfish add bigbio/sdrf-skills