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

The description adds significant behavioral context beyond the annotations. It explains the paywall behavior: without a valid bundle_key, a teaser is returned; with it, the full report is provided. This goes beyond the readOnly and idempotent hints, offering transparency about data access and limitations. No contradictions with annotations.

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 highly concise: three sentences that are front-loaded with usage guidance, followed by details on the paywall behavior. Every sentence provides critical information without redundancy or filler. This is an optimal length for the tool's complexity.

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 has an output schema (as indicated by context signals), the description does not need to detail return values. It covers the two operational modes (with/without bundle_key) and mentions key data points returned (citation rates, position, etc.). This is complete for an agent to understand the tool's behavior and output.

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?

The input schema already provides high-quality descriptions for both parameters (bundle_key and brand_domain), covering 100% of the parameters. The description does not add new semantic information about the parameters; it only references the bundle_key in the behavioral note. Therefore, baseline score of 3 is appropriate.

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 states clearly that the tool retrieves citation data from AI search platforms. It starts with 'Use this when a customer wants to see how AI search platforms cite them,' which directly defines the purpose. However, it does not explicitly distinguish this tool from sibling tools, so it meets the standard for a clear purpose but falls short of the highest tier.

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?

The description provides clear context on when to use the tool ('when a customer wants to see how AI search platforms cite them') and warns against misuse ('Citation data is paid intelligence, not a free reconnaissance tool'). It does not explicitly mention when not to use it or alternatives, but the guidance is sufficient for most scenarios.

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