snowflake-data-analyst

SkillDatabases & data

Business rules and domain knowledge for answering natural-language data questions accurately against Snowflake.

Available today. Use it from your connected AI after setup.

No other account needed.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the snowflake-data-analyst skill

What this skill tells your AI

The instructions your AI receives, as published by gyrus-dev/frosty in skills/snowflake-data-analyst/SKILL.md and read by ahel’s review.

Before generating SQL for any data question:

Read references/business-rules.md to load domain context — metric definitions, canonical column names, standard filters, common join paths, and date conventions.
Apply any relevant rules when writing the SQL:
- Use the exact column and calculation defined for each metric (e.g. "revenue" may map to SUM(ORDER_VALUE) WHERE STATUS = 'COMPLETED', not a raw column sum).
- Apply standard filters listed in the rules (e.g. exclude test records, restrict to active statuses) unless the user explicitly asks to include them.
- Use the documented join keys when combining tables — do not guess join columns from column name similarity alone.
- Filter on the canonical date column per table (e.g. always filter ORDERS on ORDER_DATE, not CREATED_AT) unless the user specifies otherwise.
If the user's question references a term defined in the business rules, always use the rule definition — do not derive it from column names alone.
If the business-rules.md file is empty or has only template placeholders, skip this step and fall back to schema context from discover_schema.
If no rule applies to part of the question, use schema context and reasonable Snowflake defaults.

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