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

Beyond the readOnly/idempotent annotations, the description clarifies that absence from the list means not measured rather than zero, states the weekly re-measurement cadence, and specifies licensing/attribution and lack of rate limits. These add meaningful behavioral context without contradicting 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 opens with a clear purpose sentence, then uses short labeled paragraphs for usage, exclusions, and data semantics. No filler; each sentence contributes distinct information (scope, absence semantics, refresh, licensing).

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 zero-parameter lookup tool, the description covers all necessary context: what the list contains, how to use it, what it deliberately omits, the interpretation of absence, coverage scope, update frequency, and usage terms. The output schema handles return details, so no further description is needed.

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 tool has zero parameters, so the description correctly omits parameter guidance. With no parameters, the baseline is 4; there is nothing for the description to add beyond what the empty schema already implies.

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 explicitly states 'The names and slugs of every brand in the DABLOCK index' with 'nothing else,' positioning it as a pure lookup table. It distinguishes from siblings by noting 'No scores, no ranks' and naming get_visibility_index as the alternative for measurements.

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 two concrete use cases ('turn a brand name into the slug get_brand_visibility needs' and 'answer whether a brand is tracked') and an explicit do-not-use ('Do NOT use it when you want figures') with the alternative named. Also notes niche coverage difference.

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