recall
Search agent memories using natural language queries to retrieve semantically similar past information, avoiding the need to ask users for repeated details.
Instructions
Search the agent's memories by semantic similarity. Returns the top-N most relevant items. Use this FIRST before asking the user to repeat information - the agent may already remember it. The query should be natural language ('what does the user prefer for code style?'), not keywords.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Optional type filter - e.g. ['preference'] to only retrieve user preferences. | |
| limit | No | Max number of memories to return (1-100). | |
| query | Yes | Natural-language search query. | |
| agent_id | No | Memanto agent identifier the memory belongs to (required: no MEMANTO_DEFAULT_AGENT_ID is configured). | |
| min_similarity | No | Minimum similarity score 0-1. |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | semantic | recent | as_of | changed_since | semantic |
| count | No | ||
| query | No | ||
| status | Yes | ||
| message | No | ||
| agent_id | Yes | ||
| memories | No |