Data Quality Auditor

Systematic, read-only data-quality checks against Fabric — nulls, duplicates, outliers, freshness, schema — with a 0-100 score.

Build an agent that connects to your Fabric workspace, queries target datasets, and runs a battery of quality checks — completeness, uniqueness, freshness, consistency, outliers, referential integrity, and schema validation. It uses a data agent to read schemas, row counts, and statistics, then code interpreter to run each check, classify findings by severity (critical/high/medium/low), and compile a scored report. The output leads with an Overall Quality Score (X/100) and a findings table — e.g. | Check | Finding | Severity | Table.Column | — so the most important issues are visible at a glance. The agent never modifies, deletes, or writes to any data source.

This is an autonomous checklist execution with severity classification pattern using numbered-rule prompt structure. Each rule maps to a phase — identity, input, retrieval, checks, severity, output, quality rules — so behavior is fully predictable: same checks, same order, same thresholds every run. The prompt enforces read-only operation and handles inaccessible tables, large datasets requiring sampling, and the discipline of reporting what was checked and what wasn't. Because checks run in code, the report is a draft for the data owner to verify.

This pattern applies anywhere an agent runs a systematic, repeatable audit against a data source and produces a scored report. Common scenarios for this pattern:

• ETL pipeline output validation
• Data-migration verification
• Dashboard data-source health checks
• Warehouse table profiling for new consumers
• Periodic data-governance reporting

This manifest uses: data agent, code interpreter

How to build autonomous agents using numbered rules prompt structure for scored audit report output.

This agent manifest is sample code subject to Azure's licensing terms for Distributable Code under the Universal License Terms for Online Services .

IMPORTANT! This manifest is for educational and experimentation purposes. Resulting agents are not production ready. Review all provided resources and carefully test agent behavior in the context of your use case. Agents you create may be subject to legal and regulatory requirements, may require licenses, or may not be suitable for all industries, scenarios, or use cases. By using any manifest, you are acknowledging that resulting agents and other output are solely your responsibility, and that you will comply with all applicable laws, regulations, and relevant safety standards, terms of service, and codes of conduct. Learn more .