list_entity_mentions

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

The description discloses the return fields (sentiment, bucket, linkback) and implies a read-only operation, which is sufficient given no annotations. However, it could mention ordering (likely chronological) and any pagination 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?

Two sentences: the first describes the output, the second states the required parameter and use case. No redundancy, front-loaded with key 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?

For a list tool with good schema and no output schema, it adequately describes the outputs and required input. It misses explicit mention of sorting order or pagination limits, but these are inferable or covered by the parameter 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 coverage is 100% with clear descriptions for each parameter. The description reinforces that 'slug' is required but adds no new semantic information beyond what the schema provides.

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 clearly states it provides a timeline of editorial mentions with sentiment score, bucket, and article linkback, differentiating it from other tools that might aggregate sentiment or provide single articles.

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 specifies the required field 'slug' and suggests usage for reconstructing narrative arcs, giving good context for when to use, though it doesn't explicitly exclude alternative tools or mention when not to use.

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