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Memory Search

memory_search

Search shared agent memory semantically with a natural-language query; filter by time, agent, or source to retrieve relevant context.

Instructions

Semantic search across shared memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesnatural-language query
sinceNoISO timestamp lower bound on metadata.timestamp
top_kNonumber of results (default 5, max 50)
agent_filterNorestrict to a single agent label stored in metadata.agent
source_filterNorestrict to a metadata.source value (e.g. 'sessions', 'memory')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. "Semantic search" implies ranking by similarity but says nothing about scoring, result ordering, whether the search spans all agents/sources by default, permission requirements, or whether "shared memory" implies cross-agent visibility. Only the bare minimum is conveyed.

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

Conciseness4/5

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

A single front-loaded sentence fragment with zero filler, which is efficient. It is arguably too terse for a five-parameter tool, but no sentence is wasted.

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

Completeness2/5

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

An output schema exists, so return values need not be explained. However, for a five-parameter semantic retrieval tool with no annotations and four distinct filter parameters, the description leaves the agent without any guidance on default scope, ranking semantics, or routing versus memory_stats.

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 description coverage is 100%, so all five parameters (including since, top_k, agent_filter, source_filter) are already documented in the schema; baseline 3 applies. The description adds no additional meaning such as default scoping behavior or how filters combine.

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

Purpose4/5

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

States a specific verb ("search") and resource ("shared memory") with the retrieval modality ("semantic") made explicit, which is more than a tautology. It does not name or contrast with any sibling, though the read-only nature of search makes it distinguishable from memory_add/update/forget on the surface.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no statement of what this tool is for relative to memory_stats (the other read-oriented sibling), and no exclusions. The agent must infer that this is the retrieval path while the others are mutation paths.

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