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

Annotations already flag read-only, open-world, idempotent, and non-destructive behavior, so the description only needs to add non-obvious context. It adds 'Cached 5 min' (stale data window) and 'methodology disclosure', which are useful beyond structured annotations. No contradiction with annotations.

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?

Two short sentences front-load the counters and add only the cache and methodology caveats. No filler, no repetition of schema or annotations.

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?

An output schema exists, annotations are rich, and no parameters require explanation. The description covers data scope, freshness via 'Cached 5 min', and methodology disclosure. This is complete for a no-input stats tool.

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 fully self-describing with additionalProperties false. The description therefore does not need to explain inputs. Baseline 4 applies.

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 'Cumulative public counters of GBLIN's x402 endpoints' and enumerates paid calls, unique payer wallets, USDC earned, and methodology disclosure. This clearly identifies the tool as an aggregate stats endpoint, distinct from receipt/risk/info siblings. The metric scope is unambiguous.

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 'cumulative public counters' phrasing and 'Cached 5 min' note establish when this tool is appropriate: for aggregate, quick, read-only metrics. It does not explicitly name alternatives, but no exclusions are needed for a zero-parameter stats endpoint. The context is clear enough for selection among siblings like receipts.get.

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