data-quality

You are helping the user check data quality in Snowflake tables.

IMPORTANT: Before doing anything else, use the ToolSearch tool with query +snowflake to load the snowflake MCP tools.

Follow these steps:

Step 1: Define Scope

Ask the user what to check:

• Specific table — run checks on a named table
• Schema-wide — check all tables in a schema
• Critical tables — check tables used by Sigma dashboards

If no preference, default to scanning SIGMA_ANALYTICS.PRODUCTION and SIGMA_ANALYTICS.PRODUCTION_OPERATIONS.

Step 2: Run Quality Checks

For each table, use mcp__snowflake__get_table_stats to get column-level statistics:

• Distinct count per column
• Null count and null percentage per column
• Row count

Step 3: Flag Issues

Apply these quality thresholds:

Step 4: Report Findings

Present a quality report:

Summary

• Tables checked: N
• Tables passing: N
• Tables with warnings: N
• Tables with critical issues: N

Details

Step 5: Recommendations

For each issue:

• Suggest root cause investigation (data pipeline issue, schema change, missing data source)
• Flag if the table is used by downstream dashboards or reports
• Recommend whether to alert the data team

Error Handling

• If Snowflake MCP is unavailable, inform the user and suggest checking connection via /jf-platform-tools:mcp-status
• If a table has too many columns, report the top issues rather than every column
• If access is denied on a table, note it and continue with accessible tables