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

With no annotations provided, the description carries the full burden of behavioral disclosure. It comprehensively discloses pricing model (per-character, no minimum), model-specific rates, BTC-pegged pricing with hourly re-quotes, the 402 challenge as authoritative, payment via Bitcoin Lightning with no API key, stable endpoints that auto-upgrade models, and support for document/vision inputs. This is far beyond typical descriptions.

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 with valuable information, well-organized, and every sentence adds critical usage or behavioral detail. It is longer than average but appropriately so given the tool's payment flow, model choices, and special features. The structure front-loads the primary purpose before diving into pricing and requirements.

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 tool with 8 parameters, no output schema, and no annotations, the description is remarkably complete. It covers the tool's purpose, model options, pricing mechanism, payment requirements, special capabilities (document Q&A, vision), model upgrade behavior, and authentication (none required). It leaves little ambiguity for the agent to invoke the tool correctly, even explaining the exact prompt requirement for payment creation.

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?

Although schema description coverage is 100% (baseline 3), the description adds meaningful context for parameters beyond the schema: it explains fileContext for document Q&A, imageBase64 for vision analysis (best model only), and clarifies that omitting modelId defaults to the best model. This goes beyond the schema's field descriptions and helps the agent understand parameter usage nuances.

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 'Generate text using frontier AI language models' – a specific verb with a resource (text generation using AI models). It further distinguishes itself from sibling generation tools (image, music, video) by naming specific text models and features like document Q&A and vision analysis, making its purpose 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 provides clear context on when to use this tool: for text generation, document Q&A, and vision analysis. It also explicitly mentions the prerequisite of create_payment with toolName='generate_text' and exact prompt. However, it does not explicitly mention alternatives or when not to use it, so it falls just short of a 5.

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