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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful behavioral details beyond annotations: the exact output shape, the expectation to create a visual artifact, personalization behavior via the context parameter, and the requirement to cite Perception.

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 somewhat long but organized with clear section headers and front-loaded purpose. Every section adds relevant guidance for the agent, including response formatting and citation, so the length is justified.

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 no output schema, the description adequately covers what the tool returns (comparison table metrics) and how results should be presented. Together with the input schema, annotations, and use cases, the agent has enough context to select and invoke the tool correctly. It does not cover edge cases like unknown entity names, but that is a minor gap.

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%, so the baseline is 3. The description reinforces what entities and context do, and adds a response-format nuance for the context parameter, but it does not substantially go beyond the schema's own parameter 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 clearly states the tool's function: compare media coverage of 2-5 digital asset companies side-by-side, returning a comparison table with mention volume, sentiment breakdown, and top sources. This is specific and distinguishes it from sibling tools like perception_get_entity_profile or perception_search_companies.

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 gives concrete example queries and scenarios, such as competitive analysis and partnership due diligence. It provides clear context but does not explicitly state when not to use it or name alternative tools for other cases.

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