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mem_search

Search stored skill memory by title, body, tag, or topic. Filter results by kind or project, and receive top-ranked matches with snippets using bilingual English-Russian stemming.

Instructions

Full-text search across skillmem memory. Uses FTS5 BM25 over titles + bodies + tags + topics with English and Russian Snowball stemming. Returns top-N results with rank and snippet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional filter: feedback / project / reference / user / note.
limitNo
queryYesSearch query.
projectNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.5

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the search algorithm (FTS5 BM25), the fields searched (titles, bodies, tags, topics), stemming languages, and the return format (top-N results with rank and snippet). This goes beyond the schema and provides useful behavioral insight. However, it does not explicitly state that the operation is read-only or non-destructive, which is a minor gap given the lack of annotations.

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 two sentences, highly concise, and front-loaded with the core purpose. It packs the search scope, algorithm, stemming, and return details into minimal words without redundancy. Every clause adds value.

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?

Given the tool has 4 parameters, no output schema, and no annotations, the description covers the search mechanics and return format but omits important context like how to use the project filter, default limit behavior, pagination, or read-only nature. For a search tool this is adequate but not exhaustive; an agent could call it correctly for simple queries but might misjudge filter usage or limit semantics.

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 only 50% (query and kind have descriptions; limit and project do not). The description mentions 'top-N results', which loosely hints at the limit parameter, and the search scope implies the query parameter, but it does not explain the project filter or how limit controls N. With half the parameters undocumented, the description should compensate but fails to fully do so, particularly for project which is completely absent from the text.

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 'Full-text search across skillmem memory', which is a specific verb-resource pair. It distinguishes itself from sibling tools like mem_get (retrieval by ID) and mem_list (listing) by focusing on search. It also adds technical specifics (FTS5 BM25, stemming) that reinforce its unique role.

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 description implies usage for searching but does not explicitly state when to use this tool versus alternatives. There is no mention of 'use this when you need to search' or exclusions like 'for exact ID lookup use mem_get'. The purpose is clear enough, but the lack of explicit routing guidance means the agent must infer context.

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