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

Goes well beyond the readOnly/openWorld annotations by disclosing the paid access model ($0.01 USDC per call via x402 on Base or Solana), the data source (LiteLLM's open price file, MIT), coverage of history from January 2026, and that results are signed. Payment requirement and provenance are exactly the behavioral facts an agent must know before calling.

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?

Front-loaded with the core resource and mode split, then supporting facts. Dense and largely waste-free, though the trailing provenance/payment/source clauses are stacked into one long paragraph that could be split for scanability.

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?

For a 7-parameter, no-output-schema tool it conveys the two response shapes (history/other-provider comparison vs filtered sorted list), the sorting options, and the payment prerequisite. Main remaining gap is the undefined 'limit' and 'mode' parameters.

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 description coverage is 0%, so the description carries the burden. It explains model, provider, min_context and max_input semantics implicitly through the filtering sentence, but never defines 'mode' (the only enum-ish behavioral knob) nor 'limit', leaving two of seven parameters opaque.

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 resource (AI model prices per million tokens, broken out by input/output/cache/batch, with context window) and a scale (~4,000 models across providers). It also names the two operating modes (with model= vs without), so an agent can immediately tell what it retrieves.

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?

Clearly partitions usage: 'With model=: its price history and the same model on other providers. Without: a list filtered by provider, mode, min_context and max_input price.' That is explicit when-to-use guidance for both branches, though it never references alternatives among the sibling tools.

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