Metadata harmonization starter
A framework for discovering, compiling, and validating reusable skills for scientific agents.
npx -y skills add ma-compbio-lab/SkillFoundry --skill metadata-harmonization-starterAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
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Metadata Harmonization Starter
Use this skill to harmonize small metadata tables with inconsistent column names and categorical labels into one canonical TSV plus a compact JSON summary.
What This Skill Does
- reads one or more tabular metadata files
- applies a JSON mapping from source columns to canonical fields
- normalizes selected categorical values such as
sexandcondition - writes a harmonized TSV and a machine-readable summary
When To Use It
- when you need a starter for
metadata-harmonization - when multiple small test fixtures use different metadata headers
- when you want deterministic harmonized outputs before validation or format conversion
Run
python3 skills/data-acquisition-and-dataset-handling/metadata-harmonization-starter/scripts/run_metadata_harmonization.py \
--input skills/data-acquisition-and-dataset-handling/metadata-harmonization-starter/examples/cohort_a.tsv \
--input skills/data-acquisition-and-dataset-handling/metadata-harmonization-starter/examples/cohort_b.tsv \
--mapping skills/data-acquisition-and-dataset-handling/metadata-harmonization-starter/examples/column_mapping.json \
--out-tsv scratch/metadata-harmonization/harmonized_metadata.tsv \
--summary-out scratch/metadata-harmonization/harmonized_metadata_summary.json
Notes
- The starter keeps the mapping external so the same script can be reused for other tiny fixtures.
- Canonical rows are sorted by
sample_idto keep committed outputs deterministic.