teach

# Teach ## Purpose Learn a reusable pattern from an example file. The user shows you a well-written artifact (model, query, config), and you extract the patterns worth following. ## Workflow 1. **Identify the file**: The user provides a file reference (e.g., `@models/staging/stg_orders.sql`). Read the file. 2. **Analyze patterns**: Extract the structural patterns, NOT the specific content. Focus on: - File structure and organization (sections, ordering) - Naming conventions (prefixes, suffixes, casing) - SQL patterns (CTE vs subquery, join style, column ordering) - dbt conventions (materialization, tests, config blocks) - Common boilerplate (headers, comments, imports) - Data type choices - Error handling patterns 3. **Present findings**: Show the user what you learned in a structured list. Be specific: - Good: "Column order: keys first, then dimensions, then measures, then timestamps" - Bad: "Good column ordering" 4. **Ask for confirmation**: Let the user confirm, modify, or reject your findings before saving. 5. **Save via training_save**: Use the `training_save` tool with: - `kind`: "pattern" - `name`: A descriptive slug (e.g., "staging-model", "incremental-config") - `content`: The extracted patterns as a concise, actionable checklist - `scope`: "project" (default — shared with team via git) - `source`: The file path you learned from - `citations`: Reference to the source file ## Important Guidelines - Extract PATTERNS, not content. "Use `{{ source() }}` macro" is a pattern. "Query the orders table" is content. - Keep it concise — max 10 bullet points per pattern. If more are needed, split into multiple patterns. - Use the file's actual conventions, don't impose your own preferences. - If the file doesn't have clear patterns worth learning, say so honestly. - Do NOT make any LLM calls beyond the normal conversation flow — pattern extraction happens in your analysis, not via separate API calls. ## Usage Examples ``` /teach @models/staging/stg_orders.sql /teach staging-model @models/staging/stg_customers.sql /teach @dbt_project.yml ``` If the user provides a name (first argument before the @file), use that as the pattern name. Otherwise, infer a name from the file type and purpose.