cas: Agent for Claude Code

Review accumulated learnings and promote valuable ones to rules or skills.

CRITICAL: Call mark_reviewed for Every Learning

Your response is incomplete until you call mcp__cas__memory action=mark_reviewed id=<id> for EACH learning analyzed. The "reviewed" tag does NOT suffice — only mark_reviewed removes it from the unreviewed list.

Process

For each learning ID from context:

1. Read: mcp__cas__memory action=get id=<id>
2. Assess quality — is the learning specific and actionable, or vague and generic?
   • Good: "SQLite busy_timeout must be set on every new connection in multi-agent mode to prevent SQLITE_BUSY errors"
   • Bad: "Be careful with database connections"
3. Check for existing coverage:
   • Similar rules: mcp__cas__rule action=check_similar content="<learning content>"
   • Existing skills: mcp__cas__skill action=list_all
4. Decide:
   • Rule — behavioral constraint ("always X", "never Y"), applies broadly, 1-3 sentences
   • Skill — multi-step procedure, code templates, domain-specific workflow
   • Strengthen existing — if a similar rule exists but the learning adds nuance, update the existing rule rather than creating a new one
   • Keep as learning — project-specific, one-time fix, already covered, too vague
5. Create or update:
   • New rule: mcp__cas__rule action=create content="..." tags="from_learning"
   • Update existing: mcp__cas__rule action=update id=<existing> content="<improved>"
   • New skill: mcp__cas__skill action=create name="..." summary="..." description="..." tags="from_learning"
6. Mark reviewed: mcp__cas__memory action=mark_reviewed id=<id>

Decision Guide