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

No annotations are present, so the description carries the full disclosure burden. It does add useful behavioral context: the data is live, the endpoint is public and unmetered, and it explicitly says the tool never invents completeness percentages or a brand_audit punch list. This goes beyond a simple action statement, though it stops short of describing error behavior or response format details.

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 a single compact sentence that front-loads the core purpose, adds an endpoint alias, and includes a meaningful negative constraint. Every clause adds value and there is no redundant or filler wording.

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 parameterless public report tool with no output schema, the description provides a strong overview of the returned content and explicitly excludes certain false outputs. It lacks some detail like output formatting or error cases, but given the low complexity and zero parameters, it is complete enough for an agent to select and invoke the tool confidently.

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 and the schema is empty, so there is no parameter information to clarify. Per the baseline for parameterless tools, a score of 4 is appropriate; the description does not need to compensate for undocumented parameters.

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 identifies the tool as a public transparency report and specifies exactly what it returns: live D1 census/identity/remote/protocol/adoption/pipeline counts plus method notes. It also references the equivalent HTTP endpoint (GET /v1/coverage), which removes ambiguity and helps distinguish it from the other census_* siblings.

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 implies when the tool is appropriate—public transparency reporting, unmetered access—but it does not explicitly state conditions or name alternatives among the sibling tools. An agent can infer this is the go-to for coverage counts, but there is no direct when-to-use vs when-not-to-use guidance.

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