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search_memory

Cherche dans la mémoire du persona.

Pipeline grep + BM25 + dense (embeddings) + RRF + scoring d'importance.
Retourne les chunks les plus pertinents au-dessus du seuil. Filtrage scope
souple : si project_scope fourni, ne remonte que les chunks de la mémoire
globale (scope=NULL) + ceux de ce projet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes
persona_slugNosoov
project_scopeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and discloses rich behavioral context: the retrieval pipeline (grep, BM25, dense embeddings, RRF, importance scoring), that it returns only chunks above a threshold, and precise scope-filtering semantics for project_scope. It implies read-only nature but does not explicitly state side-effect safety or any 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 front-loaded with purpose, followed by pipeline details, return behavior, and scope filtering. It is efficient and information-dense, though the pipeline enumeration could be considered slightly verbose for tool selection purposes.

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

Completeness3/5

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

An output schema exists, so return format need not be explained. However, the absence of annotations and 0% schema description coverage means the description should cover parameter semantics and read-only safety more fully; it only addresses project_scope behavior and leaves k and persona_slug unexplained.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for all parameters. It thoroughly explains the behavior of project_scope, but provides no meaning for 'k' (result count), 'query' (though obvious), or 'persona_slug' (default 'soov'), leaving three of four parameters undocumented in both schema and description.

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 ('Cherche') and resource ('mémoire du persona'), and adds pipeline details that distinguish it from generic search. However, it doesn't explicitly differentiate from any sibling tool, though none of the listed siblings are competing search tools.

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?

The description implies the tool is for searching memory but offers no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or conditions that would select this tool over others.

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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