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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals non-obvious behavior: sentiment scoring, result summarization, and avoidance of verbatim echoing. It could add more about result shape or rate limits, but the output schema reduces that need.

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 dense sentences with no filler. The query examples are front-loaded, followed by purpose, alternative routing, and output expectations — all useful and directly actionable.

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 low complexity, the presence of an output schema, and no annotations, the description covers purpose, usage context, parameter syntax, and output behavior. The only notable gap is inline semantics for limit/latest, which are reasonably inferable from their defaults.

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 0%, so the description must compensate. It explains the `query` parameter well with operator examples, but gives no meaning or guidance for `limit` or `latest`, which are only visible as typed defaults in the schema.

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 uses a specific verb ('Search X'), names the resource, and gives concrete query examples. It also differentiates itself from siblings by noting it is a general-purpose search with sentiment scoring, unlike analyst_views.

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?

It explicitly states when to prefer analyst_views ('when the user cares about specific accounts'), giving the agent a clear routing condition. It also instructs how to present results: summarize, don't echo tweets verbatim.

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