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

Beyond the annotations (readOnly, idempotent, openWorld), the description discloses payment behavior ($0.02 per call), the PAYMENT_REQUIRED failure mode without credit, the free sample mode, and the behavioral edge case where issuers without third-party attestation return supply only with confidence 'none'. These traits materially affect invocation and result interpretation.

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: purpose and output fields, usage context, parameter guidance, edge-case behavior, pricing, and sample mode are all covered with no filler. The most important information is front-loaded.

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 output schema exists, the description does not need to explain return values. It covers enough context for successful invocation: parameter roles, month selection, cost/failure modes, sampling, and the confidence-none case. The description is complete for a tool of this complexity.

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?

Schema coverage is 100%, so the schema already documents each parameter. The description adds useful semantics by explaining that 'period=YYYY-MM selects an earlier month', that symbol or issuer can be passed, and that sample=true provides a free example response. This adds value beyond the schema without being redundant.

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 a precise statement: it returns the latest parsed reserve attestation for one stablecoin issuer as JSON, naming key fields such as as_of, total reserves, composition, attestor, source_url, supply, and reserve ratio. This clearly identifies the operation and resource, and the data-domain focus distinguishes it from the sibling stablecoin_list_issuers.

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 to use the tool when an agent needs machine-readable backing data instead of the issuer's PDF, and it explains how to select months and sampling. It does not explicitly state when not to use it or direct the agent to an alternative tool, but the usage context is clear enough for selection.

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