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skill-template
// Load when copying this directory to bootstrap a new OmicsClaw v2 skill (rename, fill in, then `git add`). Skip when an existing skill already covers the request.
// Load when copying this directory to bootstrap a new OmicsClaw v2 skill (rename, fill in, then `git add`). Skip when an existing skill already covers the request.
| name | skill-template |
| description | Load when copying this directory to bootstrap a new OmicsClaw v2 skill (rename, fill in, then `git add`). Skip when an existing skill already covers the request. |
| version | 0.1.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["template","scaffold","v2"] |
The user has <input shape> and wants <output shape>. Pick this skill
when <distinguishing condition>. For <adjacent capability> use
<sibling-skill> instead.
| Input | Format | Required |
|---|---|---|
| Primary input | <.h5ad / .csv / .vcf / …> | yes (unless --demo) |
| Output | Path | Notes |
|---|---|---|
| Primary table | tables/<name>.csv | one row per <unit> |
| Report | report.md + result.json | always |
--input <file>) or generate a demo (--demo).obs[X] keys; raise ValueError(...) early.--method backend.tables/<name>.csv (<script>.py:<L>) + report.md + result.json.# Demo
python omicsclaw.py run REPLACE_SKILL_NAME --demo --output /tmp/REPLACE_SKILL_NAME_demo
# Real input
python omicsclaw.py run REPLACE_SKILL_NAME \
--input <data.ext> --output results/ \
--method <method-name>
references/parameters.md — every CLI flag, per-method tunablesreferences/methodology.md — the WHY behind the algorithmreferences/output_contract.md — tables/X.csv + result.json schema<sibling-1> (upstream), <sibling-2> (parallel), <sibling-3> (downstream)LLM-grounded biological interpretation of a verified typed consensus run. Reads the typed run dir + the original adata, runs inline per-cluster DE, looks up markers in a bundled tissue-keyed marker DB, and asks the chair LLM to (γ) name each cluster's likely cell type with mandatory marker citations and (β) recommend top-3 next-step skills with mandatory evidence_refs. Output banner [A+I: Interpreted on verified consensus]. Failure-mode contract per ADR 0012.
Multi-resolution typed consensus over sc-clustering. Fans out leiden / louvain at several resolutions in parallel, scores members by silhouette + cross-method NMI, runs kmode / weighted / LCA consensus on the surviving base clusterings, and emits a verified report carrying the mandatory A-path banner per ADR 0010.
Multi-method consensus over spatial-domains. Fans out 5 methods in parallel, computes a SACCELERATOR-style base-clustering ranking, runs typed consensus (kmode / weighted / LCA), and emits a verified consensus report with the mandatory A-path banner per ADR 0010.
Load when scaffolding a NEW OmicsClaw skill from a natural-language request — generates the skill directory layout (SKILL.md, parameters.yaml, references/, tests/) under the chosen domain. Skip when modifying an existing skill (edit its files directly) or when only routing a query (use `orchestrator`).
Load when routing a natural-language omics query to the correct domain skill across spatial / singlecell / genomics / proteomics / metabolomics / bulkrna domains via keyword / LLM / hybrid matching. Skip when the target skill is already known — invoke that skill directly.
Load when extracting gene programs (NMF / cNMF factorisation) and per-cell program usage scores from a non-negative scRNA AnnData. Skip when ranking marker genes per cluster (use sc-markers) or for inferring TF → target regulons (use sc-grn).