checkpointlisted

Save the current session to TokenMizer graph memory. ## What to do 1. Ask the user for a session ID if not provided (suggest a slug based on what you're working on, e.g. "auth-service", "data-pipeline", "my-project") 2. Call the TokenMizer checkpoint API: ```bash curl -s -X POST "http://localhost:8000/api/checkpoint?session_id=$ARGUMENTS" \ -H "Content-Type: application/json" ``` 3. Show the user what was saved: - Checkpoint ID - Number of nodes in graph - Resume token count - The resume context block ## If TokenMizer is not running Tell the user to start it first: ```bash tokenmizer serve # or python3 -m tokenmizer.api.app ``` ## Session ID rules - Use lowercase slugs: `auth-service` not `Auth Service` - Keep it short and meaningful - Same ID across sessions for the same project ## Example output to show user ``` ✅ Session 'auth-service' saved Checkpoint: ckpt_a3f9b2 Nodes: 14 (6 tasks, 4 decisions, 3 files, 1 error) Resume size: 247 tokens Resume context: Goal: Build FastAPI auth service with JWT Done: Project setup | User model | Login endpoint | Fix 422 In progress: Refresh token rotation Decided: PostgreSQL | bcrypt | Redis for tokens Files: api/auth.py, api/models.py, config.py Continue: Implement token refresh endpoint ``` If $ARGUMENTS is empty, ask: "What should I call this session? (e.g. my-project)"