Frictionless tabular validation starter
A framework for discovering, compiling, and validating reusable skills for scientific agents.
npx -y skills add ma-compbio-lab/SkillFoundry --skill frictionless-tabular-validation-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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Frictionless Tabular Validation Starter
Use this skill to validate a small CSV or TSV table against a simple Frictionless schema and emit a compact machine-readable error summary.
What it does
- loads a tabular input file plus a JSON schema descriptor
- runs
frictionlessvalidation from the repo-manageddata-toolsprefix - reports row counts, field names, and normalized validation errors
When to use it
- you need a verified starter for
data-validation - you want a deterministic schema-validation smoke fixture for tabular scientific data
- you need structured validation output before downstream ingestion or conversion
Example
./slurm/envs/data-tools/bin/python skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/scripts/run_frictionless_tabular_validation.py \
--input skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/examples/toy_people_valid.csv \
--schema skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/examples/toy_people_schema.json \
--out scratch/data-validation/frictionless_summary.json
Verification
- Skill-local tests:
python3 -m unittest discover -s skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/tests -p 'test_*.py' - Expected valid summary:
valid == true,row_count == 3,error_count == 0