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

With no annotations, the description carries the full burden. It discloses that the operation is a rate-limited, single-brand lookup, which is meaningful behavioral context beyond the schema. It does not cover auth or error behavior, but the essential characteristics are clearly stated.

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 front-load the purpose and distinguish the two metrics. Every clause adds value, including the single-brand and rate-limit caveats, with no wasted words.

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 one-parameter lookup with no output schema, the description specifies exactly what is returned (the two rates) and the constraints on invocation. Nothing an agent needs to decide whether to call it or interpret the result is missing.

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 documents the brand parameter at 100% coverage, including an example. The description adds no parameter-specific detail beyond the schema, so the baseline 3 applies.

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 ('Look up') and resource (brand's AI Recommendation Rate), with precise definitions of the two metrics returned. The description makes the tool's function unambiguous and distinguishes it from mere mention counting.

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 explicit constraints: free, single-brand lookup only, and rate-limited per anti-scrape policy. It does not name alternatives, but with no siblings this is sufficient context for when the tool should be used.

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