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Recall XMemo memory

recall
Read-onlyIdempotent

Search and recall the most relevant saved memories using a natural-language query to provide context from prior preferences, facts, decisions, or project history.

Instructions

Recall the few most relevant saved memories before answering, when prior preferences, known facts, past decisions, or project context may directly affect the response. Use recall_context when many memories are needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return.
queryYesNatural-language question or search text.
explainNoWhether to include retrieval explanation details with search or recall results.
agent_idNoOptional client-supplied agent label for memory attribution.
memory_typeNoMemory type/category filter or value, such as episodic, identity, procedural, semantic, working, auto, or %.%
path_filterNoMemory path filter; % matches all paths.%
prefer_workingNoWhether to prioritize working/session-state memories in retrieval.
agent_instance_idNoOptional stable, non-secret agent instance ID for per-client attribution.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint; description adds that it retrieves 'few most relevant' memories, providing context beyond annotations.

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?

Two sentences, front-loaded with action and context, no wasted words.

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?

With output schema present and 100% parameter coverage, description adequately covers purpose, usage, and behavioral nuance. No gaps.

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

Parameters3/5

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

Schema coverage is 100%, so description doesn't need to add parameter semantics; it doesn't, which is acceptable. Baseline score 3.

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?

Description clearly states the tool retrieves relevant memories and distinguishes from sibling 'recall_context' for many memories. Specific verb 'Recall' with resource 'memories' and context.

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?

Explicitly guides when to use (prior preferences, known facts, etc.) and when to use alternative ('recall_context' for many memories).

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

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