semantic_search

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

No annotations are present, so the description carries the full burden. It discloses the semantic nature and conceptual relatedness, but lacks details on read-only behavior, authentication needs, side effects, or result format. It adds some context beyond the schema but not enough for full transparency.

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 a single sentence of 15 words, front-loaded with the verb and resource, and contains no redundant information. Every word contributes directly to the tool's purpose.

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 simplicity (2 params, no output schema), the description adequately states the core function but does not mention what the results look like or any limitations (e.g., only searches local index). It is minimally complete but could be enhanced.

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 coverage is 100%, so the baseline is 3. The description does not add significant meaning beyond what the schema already provides for 'query' and 'limit'. The schema descriptions are already detailed.

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 verb 'search' and the resource 'local semantic vector index', and specifies the purpose: to retrieve conceptually related code snippets using natural language. This effectively distinguishes it from siblings like 'search_code' which likely perform lexical search.

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 for natural language semantic queries but does not explicitly state when to prefer this tool over alternatives like 'search_code' or 'hybrid_search'. No 'when not to use' or context examples are provided.

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