Chat completions with x402 payment

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

The description discloses significant behavioral details beyond the annotations: free tiers, free trials for first calls, payment requirement (x402 Solana USDC), the 402 response with exact price, retry instructions via _meta['x402/payment'], and non-streaming responses. Since annotations provide no behavioral hints (all false), the description carries the full burden and does so thoroughly, leaving no surprises for the agent.

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 several sentences long but every clause carries signal: free/paid behavior, 402/retry, non-streaming, mutual exclusion, model selection precedence, and usage guidance. There is no fluff or redundancy. It is front-loaded with the core purpose. It is somewhat longer than strictly necessary, but for a payment-bearing tool, the trade-off is appropriate; still not as lean as the two-sentence ideal, so a 4 is fair.

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?

The tool is moderately complex: four parameters, payment logic, model-selection ambiguity, and non-streaming constraints. The description covers the crucial behaviors (free/payment/402/retry, model/mode precedence) while leaning on the schema for parameter definitions and on the output schema for return values. It does not mention how to obtain a payment token or what happens after the retry, but those could be inferred from the 402 response with the exact price. Overall, it is sufficiently complete for the MCP context, so it's a high 'adequate' score rather than an exhaustive one.

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 important semantic detail beyond the schema: the mutual exclusivity of model and mode, the explicit 'model wins if both are sent' rule, and the significance of max_tokens in non-streaming mode. It also clarifies that messages are text-only. This clearly adds value beyond the input schema, justifying a 4.

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 specific verb and resource ('Send a chat completion request'), and later reinforces the purpose ('Use this tool to generate text'). It also positions this tool against its siblings: list_models is for inspecting models and prices, while chat_completions is for actually generating text. This makes the tool's role clear and distinguishes it without needing to open any schema.

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 tells the agent when to use the tool: to generate text, and to inspect models/prices first via the free list_models tool. It also gives implicit guidance on when not to use if the agent follows the 'inspect first' instruction. The main gap is it does not explicitly mention get_price_estimate as an alternative for pricing queries, though 'inspect models and prices' implies that separate inspection path. It's clear context but lacks an explicit exclusion statement, so a 4 (clear context, no explicit exclusions) is appropriate.

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