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

Provides rich behavioral context beyond annotations: flat $0.01 cost via x402, free pre-check endpoint, automatic refund on upstream failure, no streaming at v1, and exact payment flow (call without payment, then retry with _meta["x402/payment"]). This fully discloses the non-readOnly, open-world nature of the operation.

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 and front-loaded with the core purpose, then covers pricing, limits, and payment flow. It is appropriately sized for the complexity but could be better organized (e.g., using bullet points instead of a single paragraph).

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 absence of an output schema and the complexity of payment handling, the description is quite complete—covering pricing, refunds, limits, and payment flow. It omits the response format (e.g., choices structure), which would be helpful but is not critical for invocation.

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?

With 0% schema description coverage, the description adds some meaning: input token estimation formula, max_tokens <= 500, temperature range 0..2, and the model enum value. However, it does not explain the message role/content structure or provide detail on the messages array beyond the schema itself.

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?

States a specific verb (chat completion) and resource (open-weight GPT-OSS 120B model, openai/gpt-oss-120b), clearly distinguishing it from all siblings. The model name and compatibility are 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 clearly positions the tool as an OpenAI-compatible chat completion endpoint with specific limits (no streaming, token caps) that implicitly guide usage. It does not explicitly state when to use it versus alternatives, but no direct alternative exists among siblings.

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