Works with
Data Quality Auditor
Audit datasets for completeness, consistency, accuracy, and validity. Profile data distributions, detect anomalies and outliers, surface structural issues, and produce an actionable remediation plan. Use when the user asks to check data quality, profile a dataset, hunt outliers or missing values, or validate data before analysis or model training.
Optimized workflow
This edition turns the source methodology into a repeatable agent workflow with explicit inputs, checkpoints and deliverables.
Quality standard
- Confirm scope and missing inputs before execution
- Ground decisions in available evidence and preserve source constraints
- Return an actionable result with assumptions, risks and next steps
Agent compatibility
The same core method is packaged for Claude, Codex, GPT, Gemini, Cursor and OpenCode.
Permissions & security
Source verified · conversion tested · security signals reviewed