By bigbio
Provides an AI assistant with expert-level proteomics metadata workflows: creating, validating, fixing, and enriching SDRF files, running autonomous improvement loops, and contributing annotations to community repositories.
Use when the user wants to create or annotate an SDRF file for a proteomics dataset. Triggers on PXD accessions, requests to create SDRF, or annotation tasks.
Use when the user wants SDRF annotation to run as an autonomous retained-improvement loop over one dataset, a manifest, or a dataset class such as all PRIDE cell line or crosslinking datasets.
Use when the user wants to plan what metadata to capture for a new experiment, or discuss experimental design and SDRF strategy before creating the file.
Use when the user needs to look up cell line metadata or enrich an SDRF with cell-line-derived characteristics (organism, disease, sex, sampling site, ancestry, age). Triggers on cell line names (HeLa, MCF-7, A549, …), Cellosaurus accessions (CVCL_XXXX), or "annotate cell line" requests.
Use when the user has a completed SDRF annotation for a ProteomeXchange dataset and wants to contribute it back to the community via a PR to sdrf-annotated-datasets.
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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 brainstorming proteomics metadata in the SDRF format.
SETUP PLAN ANNOTATE VALIDATE REFINE SHARE
┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Conda │ │ Templates│ │ PXD │ │ Columns │ │ Score │ │ Convert │
│ Pip │────▶│ Strategy │────▶│ PRIDE │────▶│ OLS │────▶│ AutoFix │────▶│ PR │
│ Tools │ │ Layers │ │ Paper │ │ Rules │ │ Raw scan │ │ Pipeline │
└──────────┘ └──────────┘ └──────────┘ └──────────┘ └──────────┘ └──────────┘
/sdrf:setup /sdrf:brainstorm /sdrf:annotate /sdrf:validate /sdrf:improve /sdrf:contribute
/sdrf:templates /sdrf:fix /sdrf:convert
/sdrf:review
/sdrf:techrefine
┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Format │ │ Ontology │ │ Plain │ │ Batch │
│ Spec │ │ Lookup │ │ Lang │ │ Confound │
│ Rules │ │ Verify │ │ Concepts │ │ Replic. │
└──────────┘ └──────────┘ └──────────┘ └──────────┘
/sdrf:knowledge /sdrf:terms /sdrf:explain /sdrf:design
Instead of an AI guessing at ontology terms or SDRF rules, these skills teach it exactly how to annotate proteomics datasets — using real tools (OLS, PRIDE, PubMed) guided by the methodology of experienced annotators.
The SDRF specification data (column definitions, templates) lives in a git submodule and is read at runtime — so the skills stay current when the spec evolves.
All 16 skills are under the sdrf: namespace. In Claude Code, type /sdrf: and autocomplete will show them all.
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