Vector range search

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

Beyond the readOnlyHint annotation (which indicates safety), the description adds that results are ordered by distance, capped at limit, and reports available=false if pgvector is missing. These are critical behavioral traits.

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, minimal wasted words. Purpose is first, then use cases, then behavioral details. 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?

With an output schema present, return values are covered. The description explains threshold-based nature, ordering, capping, and a key precondition (pgvector extension). Could be more complete on supported metrics or parameter interactions, but sufficient.

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 description coverage is only 13%, and the description mentions max_distance, query_vector, and limit only implicitly ('capped at limit'). No details on format, constraints, or defaults beyond schema. The metric parameter is not explained.

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?

Clearly states it returns rows within max_distance of a query vector, distinguishing it from top-k searches. The verb 'return' and resource 'rows' are specific. Contrasts with top-k, aligning with sibling vector_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?

Explicitly lists use cases (de-dup, similarity gating, clustering pre-passes) and contrasts with top-k queries. However, it does not explicitly say when not to use this tool versus alternatives like vector_search or mmr_search.

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