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search_memory

Search persistent memories using hybrid BM25 and vector scoring, with filters for role, type, agent, date, and session. Results are reranked by Q-value to surface context that supports productive work.

Instructions

Search memories with FastEmbed + Qdrant, hybrid BM25 scoring, lifecycle filtering, and Q-value reranking

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleNoFilter by role: user or assistant
typeNoFilter by memory type
agentNoFilter by agent name
limitNo
queryYesSearch query
sourceNoFilter by source: transcript, decision, etc.
date_toNoEnd date (ISO format, e.g. 2026-04-08)
client_idNoFilter by client ID
date_fromNoStart date (ISO format, e.g. 2026-04-01)
session_idNoFilter by session ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are present, so the description carries the full burden. It does disclose ranking and filtering behaviors ('hybrid BM25 scoring', 'Q-value reranking', 'lifecycle filtering') but omits basic read-only/safety disclosure and response format. 'Search' implies non-mutating, but with 10 parameters and no output schema, more behavioral context is needed.

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

Conciseness3/5

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

The description is a single dense sentence that packs technical terms (FastEmbed, Qdrant, BM25, Q-value) without hierarchy or explanation. It is concise but not well-structured for an agent to parse, and the jargon-heavy phrasing may obscure the core functionality.

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?

With 10 parameters, no output schema, and no annotations, the description leaves ambiguity about result shape, how 'lifecycle filtering' works, and what 'Q-value reranking' means for returned results. The tool's complexity demands more context than this one-liner provides.

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 90%, so the schema already documents the parameters. The description adds only 'lifecycle filtering', which is too vague to map to date_from/date_to or other filters, providing negligible extra semantics beyond the schema.

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?

The description opens with 'Search memories', a specific verb and resource, and it is the only search tool among siblings (add_memory, log_prediction, log_outcome, memory_stats), so its role is clear. However, the rest of the description is technical jargon that doesn't add functional scope or explicitly distinguish it from the other tools.

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

Usage Guidelines3/5

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

No mention of when to use this tool versus memory_stats or add_memory, and no exclusions or conditions are stated. The intended use is implied by the verb 'Search' and sibling names, but the description offers no explicit guidance.

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