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

With no annotations, the description carries full responsibility for behavioral disclosure. It details return structure (data array with fields, meta object, similarity score) and provides example queries. While it does not explicitly mention read-only status or side effects, the search semantics and output specifics give adequate transparency for this tool.

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 well-organized with clear sections (WHEN TO USE, RETURNS, EXAMPLE) and front-loads the core purpose. It is slightly lengthy due to two example calls, but every section contributes useful information without redundancy.

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 absence of an output schema, the description compensates thoroughly by specifying the exact return fields and meta structure. It provides usage guidance, parameter examples, and behavioral context. The tool is a straightforward search, so this description leaves no significant gaps for an agent to invoke it correctly.

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 adds meaning by showing examples that combine query, limit, and min_similarity, and by linking similarity to cosine distance in the return section. This reinforces how parameters behave beyond the schema's basic descriptions.

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 a specific verb and resource: 'Semantic search over content library using natural language queries and 768-D pgvector embeddings.' This clearly distinguishes it from sibling tools like semantic_audience_search and semantic_search_observations by focusing on the content library. The 'WHEN TO USE' section further reinforces the intended use cases.

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?

A dedicated 'WHEN TO USE' section lists four concrete scenarios, such as finding content by description or discovering similar content without exact IDs. It does not explicitly name alternatives or state when not to use, but the context is clear enough to guide selection among siblings.

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