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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is safe to invoke. The description adds useful context by stating the data is public and counts are current, and by signaling that the output is machine-readable, which helps the agent set expectations.

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, front-loaded sentence with no filler. Every word adds meaning: it names the action, the output type, the audience (machine-readable), the scope (public), and the target dataset.

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 no-parameter, read-only tool with an output schema present, the description covers all essential context. An agent knows what the tool returns, that it targets the public 2b2t Atlas dataset, and that invocation has no side effects.

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 an empty input schema, so there is no parameter burden for the description to carry. Baseline 4 is appropriate because no additional parameter meaning is needed.

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 uses a specific verb ('Return') and a clearly bounded resource ('current counts and machine-readable discovery links for the public 2b2t Atlas dataset'). It clearly differentiates this from the sibling find/search/location tools by focusing on dataset-level statistics.

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 gives a clear context for use: call when you need current counts or machine-readable discovery links for the public Atlas dataset. It does not explicitly name alternatives or when-not-to-use cases, but the no-argument, dataset-level scope makes that omission minor.

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