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kb_search

Search indexed knowledge using natural-language queries to retrieve relevant documentation, concepts, and build targets. Filter by source and adjust top-k to refine results.

Instructions

Semantic search across indexed knowledge.

Args: query: Natural-language question or keyword phrase. source: Optional source name (see kb_list_sources) to filter results. If omitted, searches every configured collection. top_k: Maximum hits to return per collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
sourceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description bears the burden of explaining behavior. It adds non-obvious details: omitting source searches every configured collection, and top_k is per collection. It does not mention read-only status, auth, or rate limits, but search inherently implies a non-mutating operation and the output schema covers result structure.

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 compact and well-structured: a brief one-line summary followed by a clean Args block. Every sentence and bullet adds necessary semantic value, with no filler or repetition.

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?

The description fully covers invocation details for all parameters and references kb_list_sources for source names. The existence of an output schema means return values do not need to be described. The only minor gap is the lack of explicit guidance on choosing this tool versus kb_get or kb_reindex, but this does not prevent correct invocation.

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

Parameters5/5

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

The schema has 0% description coverage, yet the tool description fully explains all three parameters. It clarifies that query is a natural-language question or keyword phrase, source is optional and filterable via kb_list_sources, and top_k limits hits per collection. This is excellent compensation for the schema's lack of descriptions.

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 'Semantic search across indexed knowledge,' which clearly names the operation (semantic search) and the resource (indexed knowledge). It readily distinguishes this tool from siblings like kb_get, kb_list_sources, and kb_reindex, which naturally serve different operations.

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 gives useful parameter-level guidance, such as using an optional source and referencing kb_list_sources, but it does not explicitly state when to prefer kb_search over kb_get or kb_reindex. The intended usage is implied by the name and opening sentence, but no exclusions or alternative tool routing are provided.

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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