kb_search

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

No annotations provided, so description carries full burden. It discloses that results are fragments, not complete documents, and mentions citing sources. However, it does not specify behavior like how results are ranked, pagination, or any side effects. Still, for a search tool, this is reasonably transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each serving a distinct purpose: what it does, how to use it, and when to use an alternative. No wasted words, well-structured.

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

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

Given the complexity (9 parameters, no schema descriptions, no annotations), the description covers high-level purpose and guidance but fails to document parameters. Output schema exists but does not compensate for missing parameter semantics. Completeness is moderate.

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

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

Schema has 9 parameters with 0% description coverage. Description only implicitly mentions 'query' as the search term and does not explain any other parameters (top_k, domain, status, service, authority, min_score, source_type, document_type). This leaves the agent guessing about their meaning and usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it searches corporate knowledge, lists concrete use cases (architectural analysis, changes across services), and mentions specific content types (business rules, ADRs, APIs, events, runbooks). It also distinguishes from sibling tool kb_get_document for complete documents.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear instructions: use before architectural analysis, cite source_path or source_url, and notes that a fragment is evidence, not the only source of truth. Explicitly suggests using kb_get_document when the complete document is needed.

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