memory_distill
Persist a reusable convention or pattern synthesized from multiple prior memories. Store higher-signal learnings that rank above raw facts in semantic recall.
Instructions
Persist a distilled convention — a reusable learning, pattern, or runbook synthesized from multiple prior memories. Stored as kind='distilled', memory_subtype='convention' with canonical origin metadata. Use this when you've noticed a pattern across several prior facts/sessions that's worth surfacing as its own atomic learning. The new memory will rank above raw facts in semantic recall because distilled patterns are higher-signal. Provide 'supersedes' if this distillation replaces an earlier convention. The original stays in storage but is excluded from recall.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| repo | No | Repository or project surface this learning applies to. | |
| content | Yes | One-sentence reusable convention or pattern. Should be self-contained and applicable beyond a single situation. | |
| entities | Yes | Lowercase entity names this distillation applies to (services, tools, concepts). | |
| task_key | No | Task or issue key associated with this learning, if relevant. | |
| supersedes | No | ID of an earlier distilled fact that this one replaces. Old fact is marked superseded and excluded from recall. | |
| destination | No | Optional destination override. Omit to let routing rules decide. | |
| workspace_id | No | [Removed in v0.4.0] No-op. |