| name | teach |
| description | Teach your AI teammate a pattern by showing it an example file from your codebase |
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
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Identify the file: The user provides a file reference (e.g., @models/staging/stg_orders.sql). Read the file.
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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
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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"
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Ask for confirmation: Let the user confirm, modify, or reject your findings before saving.
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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.