analyzing-data
Query your data warehouse to answer business questions with cached patterns and concept mappings.
- Supports pattern lookup and caching for repeated question types, with outcome recording to improve future queries
- Includes concept-to-table mapping cache and table schema discovery via INFORMATION_SCHEMA or codebase grep
- Provides
run_sql()andrun_sql_pandas()kernel functions returning Polars or Pandas DataFrames for analysis - CLI commands for managing concept, pattern, and table caches, plus warehouse selection and kernel lifecycle control
Data Analysis
Answer business questions by querying the data warehouse. The kernel auto-starts on first exec call.
All CLI commands below are relative to this skill's directory. Before running any scripts/cli.py command, cd to the directory containing this file.
Workflow
-
Pattern lookup — Check for a cached query strategy:
uv run scripts/cli.py pattern lookup "<user's question>"If a pattern exists, follow its strategy. Record the outcome after executing:
uv run scripts/cli.py pattern record <name> --success # or --failure -
Concept lookup — Find known table mappings:
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