IBM Granite Chat ($0.02)

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

Annotations already indicate readOnly and openWorld hints. The description adds valuable information: payment model ($0.02 USDC via x402), that no IBM Cloud account is needed, and that token usage is returned. These details go beyond what annotations provide.

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, efficiently conveying the core functionality, input format, output, and pricing without redundancy. It is well-structured and front-loaded.

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 (four parameters with full schema descriptions), the description covers the essential context: input/output nature, default model, and payment. It lacks detail on response format but annotations and schema fill in gaps adequately.

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 baseline is 3. The description adds context by mentioning 'role/content message pairs' and default model, which clarifies the use of the messages array and model parameter beyond schema descriptions.

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 it is a chat completion tool using IBM Granite models. While it doesn't explicitly differentiate from sibling tools, the names of siblings (analyze, code, embed, forecast, getting_started) imply distinct tasks, so the purpose is sufficiently clear.

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 does not provide guidance on when to use this tool versus alternatives or when not to use it. It lacks explicit context for selection criteria among siblings or exclusions.

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