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

With no annotations, the description carries the full burden and does well: it discloses the flat $0.01 USDC cost on Base via x402 (a real auth/payment prerequisite), the 32,000-character input cap and 2,048-token output cap, and the default model. It omits what happens on payment failure or rate limiting, but the core behavioral profile is present.

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?

Two sentences, front-loaded with the verb and the I/O contract, then cost and limits. It is dense but nearly every clause carries information; the only slack is the parenthetical model enumeration, which the schema already lists.

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?

No output schema exists, and the description compensates by stating the return shape (reply text plus token usage). Given six optional parameters, a payment requirement, and model selection, nothing an agent needs to invoke this correctly is missing.

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, but the description adds meaning the schema does not: the 32,000-character input ceiling, the 2,048-token output ceiling, the input-shape choice between a prompt string and a messages array, and which model is the default. That is genuine value beyond the structured fields.

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 and resource (chat completion), plus the distinguishing scope ('larger models') and the I/O contract ('prompt ... in, reply text and token usage out'). An agent can distinguish it from the sibling ai_chat purely on the 'larger models' framing without opening either 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?

Pricing and model size imply this is the heavier/paid tier relative to ai_chat, but the description never names ai_chat or ai_embeddings or states a condition for choosing between them. Usage is implied rather than prescribed.

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