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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful context by explaining the tool reports the platform's current data holdings and includes freshness timestamps, which aligns with the openWorldHint. No contradiction and no hidden side effects are implied.

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 compact, front-loads the data categories, and includes a practical call-to-action in the final sentence. Every sentence contributes meaning without redundancy.

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 the tool has no parameters, rich safety annotations, and a clear list of returned coverage dimensions, the description is complete enough for an agent to know when and why to invoke it. No output schema is present, but the description enumerates the key content adequately.

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 baseline is 4. The description does not need to explain inputs and, consistent with the empty schema, implies this is a global snapshot that takes no arguments.

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 returns: a platform-wide summary of asset count, priced assets, chains, labelled addresses, social corpus size, and freshness timestamps. It also gives the functional purpose ('check whether an answer is supportable'), which distinguishes it from sibling coverage tools like get_chain_coverage and get_address_coverage.

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 says when to call it: before asserting whether an answer is supportable. It does not mention exclusions or alternatives, but the use context is clear enough for an agent to distinguish this global coverage check from more specific sibling tools.

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