{"id":70587,"plugin_id":"plugin_asdk_app_6ae058ee6cec81919329ae43b76a4c86","kind":"skill","collection_source":"plugin_package","comparison_source":null,"observed_at":"2026-10-29T12:07:54.760Z","digest":"59fb9f7360be38a8314f3f8fee4d40973b3dfe7f5d95118c58358257ca2b8228","against":null,"payload":{"description":"Inspect data quality before quantitative analysis. Use for missingness, duplicates, schema drift, invalid ranges, inconsistent units, date errors, outliers, reconciliation, and analysis-readiness.","included_files":[{"relative_path":"agents/openai.yaml","size_in_bytes":208},{"relative_path":"references/COMMERCIAL.md","size_in_bytes":751},{"relative_path":"references/PROOF.md","size_in_bytes":537},{"relative_path":"references/QUALITY.md","size_in_bytes":2262},{"relative_path":"references/ROUTING.md","size_in_bytes":504},{"relative_path":"scripts/proof_envelope.py","size_in_bytes":1023},{"relative_path":"scripts/scenario_grid.py","size_in_bytes":691}],"name":"musitu-data-quality","skill_md_contents":"---\nname: musitu-data-quality\ndescription: \"Inspect data quality before quantitative analysis. Use for missingness, duplicates, schema drift, invalid ranges, inconsistent units, date errors, outliers, reconciliation, and analysis-readiness.\"\n---\n# MUSITU Data Quality\nRead `references/QUALITY.md`.\n\n## Workflow\n1. Inventory schema and expected semantics.\n2. Measure completeness, uniqueness and validity.\n3. Check unit, date, currency and category consistency.\n4. Detect duplicates, outliers and schema/distribution drift.\n5. Reconcile totals and identities where applicable.\n6. Classify defects by impact and confidence.\n7. Block downstream analysis when defects invalidate results.\n8. Return remediation steps and residual data risk.\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}