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

Annotations provide only basic hints (readOnlyHint=false, etc.), but the description adds crucial behavioral details: input/output limits (24,000 chars, 1,024 tokens), text-only modality, no streaming, authentication via x402 payment ($0.05/call). No contradiction with annotations.

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 two sentences, front-loads key information (compatibility, models, caps, auth), and contains no extraneous words. Every sentence adds value.

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 (3 params, output schema exists), the description covers purpose, models, limits, auth, and cost. It omits return format and error handling, but the output schema likely covers the former. Overall sufficient for selection and 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?

Schema coverage is 100%, so the schema already explains parameters (model, messages, max_tokens) with descriptions. The description reinforces caps and default model but adds no new semantic detail beyond what the schema provides. Baseline score of 3 is appropriate.

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's purpose: 'OPENAI-COMPATIBLE chat completions, PRO tier — frontier models at one flat price, no API key, no account.' It lists specific models and differentiates from siblings like post_v1_chat_completions by emphasizing the PRO tier and no-account access.

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 explains compatibility with OpenAI SDK and mentions caps and payment, but does not explicitly compare with alternative tools like post_v1_chat_completions or post_llm. It implies usage for frontier models without an account, but lacks direct when-to-use guidance.

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