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

Annotations already indicate readOnly and idempotent, and the description adds meaningful behavioral context: it returns aggregated metrics and individual mentions, requires separate calls per outlet for comparisons, and personalizes analysis via the context parameter. No contradictions with the read-only annotation.

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-structured with clear sections and the core purpose is front-loaded. It is somewhat verbose and the PERSONALIZATION section mostly repeats the context parameter's schema description, but every section still contributes useful operational guidance.

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 read-only tool with no output schema, the description explains its return values, use cases, parameter behavior, comparison workflow, and citation requirements. An agent has enough information to decide when to call it and what to expect from the response.

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 using exact outlet names and mentions context personalization, but the schema already documents these semantics thoroughly. No substantial new parameter insight is added beyond 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 opens with a specific verb and resource: 'Get detailed coverage analysis for a specific media outlet.' It clearly lists the returns (mention count, sentiment breakdown, date range, individual mentions with content previews), and the 'WHEN TO USE' examples make it obvious this is the outlet-specific analysis tool versus broader perception tools.

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 use cases like 'How is Bloomberg covering crypto this week?' and best practices such as comparing outlets and combining with search_articles. It does not explicitly state when not to use this tool, so it lacks the full exclusion guidance needed for a 5.

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