train

# Train ## Purpose Learn team standards and conventions from a document (style guide, review checklist, coding standards, etc.). Extracts actionable rules and saves them as training. ## Workflow 1. **Get the document**: The user provides either: - A file reference: `@docs/sql-style-guide.md` - A URL: The full URL to fetch (use webfetch tool) - Inline text: Pasted directly in the chat 2. **Read and analyze**: Parse the document and extract: - Specific, enforceable rules (naming, formatting, prohibited patterns) - Review criteria and checklists - Glossary terms and definitions - Architectural standards 3. **Categorize**: Group findings by training kind: - `rule` — Specific do/don't rules (e.g., "Never use SELECT *") - `standard` — Broader conventions (e.g., "SQL style guide compliance") - `glossary` — Term definitions (e.g., "ARR = Annual Recurring Revenue") 4. **Present summary**: Show the user what you extracted: - Number of rules, standards, and glossary terms found - Preview of each item - Ask for confirmation before saving 5. **Save via training_save**: Save each item using the `training_save` tool. For documents with many rules, consolidate related rules into logical groups (e.g., "sql-naming-rules" with 5 rules, rather than 5 separate entries). ## Important Guidelines - Only extract ACTIONABLE items. Skip vague guidance like "write clean code." - Consolidate related rules into single training entries to avoid clutter. - Preserve the original wording when it's specific and clear. - If the document is too large, focus on the most impactful rules. - Always use `scope: project` unless the user specifies global. - Do NOT make any extra LLM calls — analysis happens in the normal conversation flow. ## Usage Examples ``` /train @docs/sql-style-guide.md /train https://wiki.company.com/data-team/review-checklist /train (then paste content inline) ```