memory-distill

memory-distill

Staging inbox is temporary — from any ingest source (staging/ingest/<id>/captured.md) or project/user staging. Distill durable facts into typed paths; discard ephemeral noise.

When staging inbox depth reaches staging_nag_threshold (default 50), agents automatically receive a nag alert in AGENTS.md and MCP tool responses to trigger distillation.

Quick Option: Auto-Distill

For fast automated triage of noise and standard facts:

• Call MCP auto_distill(limit=50, discard_noise=true)
• Or CLI: python -m agents_memory distill --auto

Full LLM Workflow

1. Call MCP get_staging_inbox(limit=20) — returns groups by source (ingest id / file).
2. For each bullet in each group, evaluate:
   • Keep (Durable Fact): Core decisions, tech stack choices, preferences, personal workflow rules, durable architecture constraints.
     • Select target kind: concept, entity, workflow, note, project, decision, proposed, implemented.
     • Assign clean slug name (and project / collection if applicable).
   • Discard (Noise / Ephemeral): One-off debug talk, temporary questions, code snippets with no lasting rule, accidental transcript dumps.
3. Call MCP distill_batch(items_json) with the classified items. Always pass through source_path (and project when present) from the inbox item so removal hits the right file:

   [
     {
       "bullet": "[Homelab @ …] Always use Tailwind v3",
       "kind": "note",
       "name": "stack",
       "project": "customs",
       "source_path": "user/staging/ingest/cursor/captured.md"
     },
     {
       "bullet": "Can you check line 40 of main.py",
       "discard": true,
       "source_path": "user/staging/ingest/cursor/captured.md"
     }
   ]
   

4. Repeat until get_staging_inbox reports "total": 0.
5. distill_batch and promote_bullet automatically sync to all IDEs/CLIs upon completion.