search_recent_mentions

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

Without annotations, the description discloses behavioral traits: two modes of operation, output contents (tweet text, author, timestamp, metrics), and pagination limits. It lacks explicit mention of rate limits or authentication requirements but covers the core behavior.

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 concise yet complete, organized logically: purpose, mode explanation, use cases, output details, and limits. No extraneous information.

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 only two parameters, full schema coverage, and an output schema, the description covers all necessary aspects: function, usage, output description, and constraints. Nothing is missing.

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 100%, and the description adds context beyond schema by explaining how the query parameter affects behavior and the meaning of max_results, including default and range.

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 explicitly states it searches for recent tweets mentioning the authenticated user or matching a custom query, clearly distinguishing two behavioral modes. It differentiates from siblings like search_tweets by specifying scope and 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?

The description provides clear use cases such as monitoring mentions and tracking brand mentions, but does not explicitly state when not to use or recommend alternatives among siblings.

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