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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context by describing the response row contents, the entities vs topics modes, and the data-source attribution requirement. This goes beyond what annotations alone convey.

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 under headers—WHEN TO USE, MODES, RESPONSE, PERSONALIZATION—and every section adds practical value. It is somewhat long, and there are minor typos, but the structure makes it easy for an agent to parse and apply.

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?

For a tool with 9 optional parameters and no output schema, the description covers the core use cases, parameter selection, response fields, modes, and even personalization guidance. An agent has enough context to invoke the tool correctly for typical media-leaderboard queries.

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 practical meaning by mapping example queries to parameter combinations (outlet, mode, limit, categories) and explaining the entities vs topics distinction. This supplements the schema with real usage patterns.

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?

States a specific verb and resource: 'Returns the top entities or topics ranked by mention count within a date range or outlet.' The 'media-leaderboard view' framing and example queries clearly differentiate it from sibling search/report tools. An agent can understand exactly what this tool computes.

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?

Provides an explicit 'WHEN TO USE' section with concrete query-to-parameter mappings, such as outlet for conferences and mode='topics' for theme coverage. It gives clear context for common use cases, though it does not explicitly name sibling tools to exclude or state when not to use this tool.

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