checkpoint

name	checkpoint
description	Save the current session to TokenMizer graph memory. Creates a persistent checkpoint with all tasks, decisions, files, and errors — resumable in any future session. Use when user says "save", "checkpoint", "remember this", "I'm done for today", or session is getting long.

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:

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:

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)"