semantic-search-docs

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 key behavioral aspects: use of AI embeddings, conceptual matching, and returning similarity scores. However, it does not mention whether the operation is read-only, any rate limits or network dependencies, or behavior when no results are found. For a search tool this is a moderate gap.

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 two sentences long, front-loaded with the core action (semantic search) and key differentiator (embeddings). Every word earns its place, clearly conveying purpose and output without verbosity.

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 tool's complexity (6 parameters, no output schema, no annotations), the description covers the essential context: what it does, how it works, and what it returns. It does not explain output structure in detail, but since no output schema exists, the return description is somewhat brief. Overall, it is reasonably complete for a search tool.

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 input schema has 100% description coverage for all 6 parameters, so the schema already provides comprehensive meaning for 'query', 'topK', 'library', 'version', 'cwd', and 'searchMode'. The description adds no additional parameter-specific semantics beyond what the schema provides, so a baseline score of 3 is appropriate.

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 clearly states the tool performs semantic search across documentation using AI embeddings to find conceptually similar content. It distinguishes itself from the sibling search-docs by highlighting the embedding-based approach and the ability to match even when exact keywords don't match. The returns (relevant documentation chunks with similarity scores) are also explicitly mentioned.

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 usage when exact keyword matching is insufficient ('even when exact keywords don't match'), providing clear context for when to choose this tool. However, it does not explicitly name alternatives like search-docs or state when NOT to use this tool, so the guidance remains implied rather than explicit.

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