blockrun_models

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

Annotations already mark this as read-only and non-destructive, lowering the burden on the description. The description adds useful context by noting that results include pricing and that the tool supports discovery and cost comparison. There is no contradiction with the annotations, and no hidden side effects are implied.

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 concise sentences with no wasted words. The core purpose is front-loaded, and the usage guidance is immediately actionable. Every sentence earns its place.

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 simple read-only listing tool with two optional parameters and no output schema, the description provides sufficient context: it names what is listed, includes pricing, and states the intended use. The schema covers filtering, and annotations cover safety, so no critical information 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 description coverage is 100%, so both parameters (category and provider) are already fully documented in the schema. The description adds no parameter-level detail, but based on the high schema coverage, the baseline 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 states a specific action and resource: 'List available AI models with pricing.' It clearly communicates that this tool is for discovery and cost comparison, which distinguishes it from siblings like blockrun_chat or blockrun_image that execute model tasks rather than list them. It does not explicitly name a sibling alternative, but the purpose is 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 gives clear context: 'Use to discover models and compare costs.' This tells an agent when the tool is appropriate, although it does not explicitly state when not to use it or mention alternatives. Still, for a simple listing tool this level of guidance is sufficient.

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