mimir_extract
Extract facts, preferences, and events from text or stored entities with a fully local rule-based extractor. No cloud or network required.
Instructions
Extract structured knowledge — facts, preferences, temporal events, episodes — from raw text or a stored entity, using a fully local, deterministic rule-based extractor (no cloud LLM, no embedding/API call, no network). Read-only: never writes to the store. Provide text, or category + key to extract from a stored entity.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | Key of a stored entity to extract from (requires category). | |
| text | No | Raw text to extract from. If omitted, category + key of a stored entity are used. | |
| category | No | Category of a stored entity to extract from (requires key). | |
| strategy | No | Extractor strategy: 'rule_based' (local heuristics) or 'none' (no-op). | rule_based |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| items | No | Extracted items, each an object with `kind` and `text`. | |
| total | No | Number of items extracted | |
| strategy | No | Extractor strategy used |