search_knowledge

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

With no annotations, the description carries the burden and discloses key behaviors: semantic similarity, optional type filtering, partial matching for company/person, and top_k default. It does not discuss permissions or edge cases, but for a search tool this is substantial and non-contradictory.

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?

The description is front-loaded with a clear purpose sentence and followed by a compact Args list. Each parameter line adds necessary detail, given the schema's empty descriptions. Slightly longer than minimal, but every line earns its place.

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?

For a search tool with an output schema, the description covers all invocation-relevant aspects: required query, optional filters, partial-match behavior, and default top_k. It does not explain result ranking, but that is likely handled by the output schema, so completeness is solid.

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?

The schema has zero parameter descriptions, but the description compensates fully by documenting every parameter, including the allowed values for 'type', partial match semantics for 'company' and 'person', and the default for 'top_k'. This goes well beyond bare parameter names.

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 opens with 'Search the knowledge base using semantic similarity', which is a specific verb, resource, and method. It clearly differentiates from sibling write tools like index_knowledge and upsert_knowledge.

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?

The description implies use for semantic retrieval but does not explicitly state when to use it vs alternatives, nor are there exclusions or when-not-to-use conditions. Given sibling write tools, the use case is understandable but not directly articulated.

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