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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds crucial behavioral context beyond annotations: the panel version freeze and denominator change, the three-run measurement per engine since panel v3, the weekly refresh cycle, and the lack of auth/rate limits. It also clarifies data licensing and attribution requirements.

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 dense but every sentence earns its place: it leads with the core definition, then usage guidance, then critical interpretative caveats, then update frequency and licensing. No redundant or filler content; it is efficiently structured with distinct logical segments.

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 zero parameters, rich annotations, and an output schema, the description covers everything needed: what data is returned, how to interpret it (panel version boundaries, noise thresholds), how often it updates, and access requirements. It even tells users not to report step movements as gains/losses, which is essential operational guidance.

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 schema coverage is trivially 100%. The description adds no parameter semantics (there are none to add) but provides valuable context about the output's scope and interpretation, which is the only meaningful semantic content for this no-input tool. Baseline for zero parameters is 4.

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 clearly states what the tool does: it returns every DABYTE release ever published, as a series per brand, with share of answer, date, and panel version. It explicitly contrasts with sibling tools: 'For the current release alone use get_visibility_index' and 'Call get_methodology for the exact step size,' distinguishing it from alternatives.

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 explicitly states when to use this tool ('Use this for any question about change — is a brand rising, when did it enter the index, how volatile is the category') and provides clear exclusions: comparability is invalid across panel versions, and small moves within noise should not be reported. It also names alternative tools for specific use cases (get_methodology, get_visibility_index).

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