ProactiveAgent

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Recall memories

memory_recall

Read-onlyIdempotent

Recall relevant long-term memories by keyword to restore session context and surface past work, preferences, or project history. Returns entries with type, importance, and similarity.

Instructions

Search long-term memories by keywords (keyword + embedding hybrid; falls back to keyword when embedding is unavailable). Returns matching entries with type, importance, and similarity. Call at the start of a new session/task (query = current topic) to restore context; also call whenever the user references past work, project history, or personal preferences.

Input Schema

TableJSON Schema

Name	Required	Description
`type`	No	Filter by type
`limit`	No	Max results, default 5
`query`	Yes	Search keyword/question
`scope`	No	Read scope: auto merged (default) / project / global

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.0Sep 7, 2026

TDQS

A5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint and idempotentHint, and the description confirms a read-only search operation with no side effects. The fallback behavior for embedding unavailability is also disclosed, adding transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loads the core purpose, and efficiently includes usage timing and return details without redundancy. It avoids unnecessary filler while still being informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema, annotations, and complete parameter descriptions, the description provides enough context for an agent to invoke the tool correctly. It includes return contents, filtering options, and usage scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters are described in the schema with clear meanings: query as the search keyword/question, type as a filter, limit as max results with default, and scope as read scope with auto/project/global options. Coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches long-term memories by keywords and returns matching entries with type, importance, and similarity. The purpose is immediately obvious and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided: call at the start of a new session/task to restore context, and call whenever the user references past work, project history, or personal preferences. This leaves no doubt about when to use the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.