gauge_demand

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

With no annotations provided, the description carries the full burden and excels: it discloses the paid nature ($0.03), x402 payment mechanism, caching strategy (7 days), the compute-first settle-after model with no charge for errors, and the behavior without an EVM_PRIVATE_KEY (returns 402 price terms). It also includes the return shape, which is critical given the absence of an output schema.

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 serves a purpose: cost, caching, return format, payment mechanics, and key requirements. No fluff or repetition. It is structured with a clear flow from functionality to operational details, making it easy to parse.

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's complexity (paid API, caching, payment setup) and no output schema, the description compensates fully by enumerating the exact return fields, explaining the payment flow, and specifying the prerequisite (EVM_PRIVATE_KEY). It covers all critical aspects an agent would need to know to invoke and understand the result.

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 baseline is 3. The description adds value by clarifying the query parameter: it's for physical-product queries and is normalized for caching. However, it does not add any information about the category parameter beyond what the schema already states, so the added value is moderate.

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 the tool computes a 'demand verdict for any physical-product query,' specifying both the action (demand verdict) and the resource (physical-product query). It also distinguishes from the sibling gauge_demand_live by noting the 7-day cache, making the purpose and scope 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 description provides clear context for when to use this tool (for demand verdicts on physical-product queries) and implicitly differentiates from gauge_demand_live by emphasizing caching and cost. However, it does not explicitly compare with other siblings or state when not to use it, so it lacks explicit exclusions or alternative recommendations.

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