train

name	train
description	Train your AI teammate on team standards from a document or style guide

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)