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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial behavior: data is re-measured weekly so results stay identical until the next release; figures are only comparable within a panel version; noise floor in small moves; and licensing/access details (CC BY 4.0, no key, no rate limit). These go beyond the annotations and are essential for correct interpretation.

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 about 150 words and packs in purpose, usage, caveats, and licensing. It is front-loaded with the core definition, then layers context and limitations. While dense, every sentence adds value; the length is justified given the complexity of interpretation.

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?

The description fully equips an agent to decide when to use this tool, how to interpret results, and what not to over-read. With an output schema present, it need not describe the return shape. The coverage of limitations, licensing, and sibling tools makes it contextually complete.

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 input schema provides no requirements. The description implicitly confirms no parameters are needed by describing the tool as returning the full series. Per the rubric, 0 params gives a baseline of 4; there is no additional parameter detail to add.

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 clear statement of what the tool returns: 'Every DABYTE release ever published, as a series per brand: share of answer at each weekly measurement with the date and panel version it was taken under.' This specifies the resource (full measurement time series) and the content. It also distinguishes from siblings by naming alternatives for current-release data and methodology.

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?

Explicit guidance is given: 'Use this for any question about change — is a brand rising, when did it enter the index, how volatile is the category.' It also provides exclusions and alternatives: 'For the current release alone use get_visibility_index' and 'Call get_methodology for the exact step size.' The description further warns when not to treat a change as meaningful, giving clear usage boundaries.

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