v1_run

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

With no annotations, the description carries the full transparency burden. It discloses cost ($0.05/call or metered), model (Claude Haiku 4.5), payment method (wallet), data handling (no storage), AI lane declaration, and spend caps. It does not detail rate limits or response structure beyond printing tokens and costs, but overall it is transparent and exceeds minimal 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 paragraph but front-loads the important cost detail. It covers pricing, model, data handling, and lane declaration without being excessively verbose. Some repetition (e.g., mentioning flat fee twice) could be tightened, but overall it is well-structured and earns its sentences.

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 3 parameters, no output schema, and no annotations, the description compensates well by explaining the payment model, model identity, data retention policy, and the presence of spend caps. It does not describe the exact output format beyond listing tokens, cost, margin, and charge, but this is sufficient for most use cases.

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 baseline is 3. The description adds minimal extra meaning: it clarifies that the prompt is sent as a single user message and mentions the default of 256 (already in schema). The cost and model information are not parameter-specific. The added value is marginal.

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 runs an LLM prompt over x402, specifying the model, cost structure, and that it returns raw model output. It effectively differentiates from sibling tools, which are all unrelated (crypto, weather, knowledge, etc.), so the purpose 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 description does not explicitly state when to use this tool versus others. While the sibling tools are diverse, the description lacks direct guidance on when to use or avoid this tool, such as mentioning that it is only for single prompts with a fixed model and no streaming. The context of paying with a wallet is clear but not comprehensive.

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