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Search this knowledge base for content relevant to a natural-language query. Returns the closest-matching snippets with their source, not an exhaustive list.

Input Schema

NameRequiredDescriptionDefault
topKNoMaximum number of results to return (1–20).
queryYesThe natural-language query to search for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that results are closest-matching snippets (i.e., ranked/approximate) rather than exhaustive, and that each carries a source. It omits read-only nature, permissions, freshness of the index, and 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?

Two compact sentences with the core purpose front-loaded and no padding. Every clause earns its place, though the return-behavior clause could have been equally brief.

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

Completeness4/5

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

For a two-parameter query tool with no output schema and full schema coverage, the description covers what it does and the shape of the return (ranked snippets with source). It is nearly complete; only auth and index-scope details are absent.

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 100%, so both parameters are already documented with types and the topK range (1–20). The description only reinforces the natural-language framing of the query, adding no syntax, weighting, or filtering 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?

States a clear verb (Search) and resource (this knowledge base) plus the input type (natural-language query). Siblings like get_service, list_services and submit_contact are unrelated operations, so no differentiation is needed, but 'this knowledge base' is slightly vague about scope.

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?

Usage is implied by the contrast with 'an exhaustive list,' which tells the agent this is a ranked-relevance lookup rather than a full enumeration. However, there is no explicit statement of when to prefer this tool or what prerequisites (auth, index scope) apply.

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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