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OpenExp

OpenExp

by anthroos
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_memory

Retrieve relevant memories using hybrid semantic, BM25, recency, and importance scoring, with lifecycle filtering by role, type, agent, source, date, and session.

Instructions

Search memories with FastEmbed + Qdrant: hybrid semantic + BM25 + recency + importance scoring with lifecycle filtering

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_memory"
  }
}

Input 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

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose a read-only search with scoring and lifecycle filtering, but leaves unexplained the result ordering, pagination, lifecycle semantics, and any access or rate limits.

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?

The description is a single dense sentence that front-loads the action and packs useful distinguishing details without filler. The main drawback is jargon like 'FastEmbed', 'Qdrant', and 'lifecycle filtering' is not unpacked, slightly reducing clarity for an agent.

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?

For a 10-parameter search tool with no output schema and no annotations, the description is too thin: it does not describe the result shape, pagination, how filters combine, or what lifecycle filtering excludes. An agent can infer high-level intent but not safely predict call outcomes.

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 high at 90%, so the baseline is 3; the description adds no per-parameter meaning beyond what the schema already provides. It does not explain how query, date filters, or role/source filters interact with the scoring behavior.

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 opens with a specific verb and resource ('Search memories') and names the retrieval/scoring strategy (hybrid semantic + BM25 + recency + importance), which clearly distinguishes it from siblings like memory_stats and add_memory. The purpose is unambiguous and not a tautology.

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?

The search intent is clear from the name and description, but there is no explicit guidance on when to use this tool over sibling alternatives, nor any stated exclusions or conditions. Usage is implied rather than instructed.

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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