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memex_recall

Read-onlyIdempotent

Retrieve stored memories about past work, decisions, or conversations by searching your memory bank with a natural-language query.

Instructions

Search stored memories for query. Call before answering questions about prior work, decisions, or past conversations. Default mode="fast" (vector search, ~0.1s); use mode="thorough" only when a fast result looks wrong or stakes are high (~3s, hybrid search). Current facts list first, superseded/expired after, marked. Every hit shows its id, status, and recorded date. Fix a stale hit with memex_correct; see its history with memex_get. Do not use this to store a new fact -- use memex_store instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo"fast": vector search (default). "thorough": hybrid search, slower, for a second opinion.fast
as_ofNoOptional ISO-8601 date or instant. Answer as memory stood then: records written later are excluded and later supersessions are ignored.
limitNoMax hits to return.
queryYesNatural-language search query.
historicalNoKeep relevance order; do not demote superseded or expired records.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read-only profile. The description adds valuable behavioral context beyond that: result ordering ('Current facts list first, superseded/expired after, marked'), the presence of id, status, and recorded date on each hit, and the mode-specific latency/behavior differences. It doesn't explicitly describe the historical flag's effect on ordering, but the schema covers its semantic, so a 4 is appropriate given the strong annotation coverage.

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 a single well-structured paragraph that front-loads the core purpose, then moves to usage guidance, then behavioral details, and finally alternative tools. Every sentence contributes new information; there is no fluff or repetition of schema content. The flow is logical and efficient.

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 tool has 5 parameters and no output schema, the description is remarkably complete. It explains when to call, how to choose modes, what the results look like (ordering, fields), and points to related tools for correcting or viewing history. The as_of parameter is documented in the schema, and the description doesn't need to repeat it. Nothing essential for an agent to use the tool correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful value beyond the schema: it explains the practical trade-off between fast and thorough modes with approximate latencies and when to choose each, and it clarifies the overall search semantics (hybrid search) not fully captured in the schema's enum descriptions. This lifts it to a 4.

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's verb and resource: 'Search stored memories for `query`.' It further specifies the use case (answering questions about prior work, decisions, or past conversations) and distinguishes itself from siblings by naming memex_correct, memex_get, and memex_store as alternatives for different actions. This leaves no ambiguity about what the tool does.

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?

The description provides explicit when-to-use guidance: 'Call before answering questions about prior work, decisions, or past conversations.' It also gives nuanced usage instructions for the two modes, stating when to prefer thorough over fast ('only when a fast result looks wrong or stakes are high'), and explicitly warns not to use this tool for storing facts, pointing to memex_store instead. This is exemplary usage guidance.

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