List model capabilities

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

Even without annotations, the description discloses an important behavioral trait: it reports codebase-wired capabilities rather than vendor claims. This helps the agent understand the data source and reliability. It does not explicitly state that the tool is read-only or describe side effects, but for a list operation this level of disclosure is reasonably transparent.

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, front-loads the core purpose, and adds only meaningful distinctions and usage examples. Every sentence earns its place without fluff or repetition.

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 list tool with no parameters and no output schema, the description gives enough context: what it lists, the source of truth, and two concrete usage cases. It could go further by describing the return format or whether listing is summary-only, but this is not a significant gap for the tool's simplicity.

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?

The tool has zero parameters, so parameter semantics are inherently not a burden. The description adds relevant context about what the returned information covers, but no parameter documentation is needed. The baseline score of 4 for zero-parameter tools applies.

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 a specific verb ('Lists') and resource ('what each model can do'), and adds a distinguishing qualifier: capabilities 'as wired up in this codebase — not what its vendor advertises.' This makes it easy for an agent to understand the tool's unique scope and differentiate it from the sibling list tools.

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 use guidance: 'Use it to see which models support grounded retrieval, and which have verified pricing.' This tells the agent when to invoke the tool, though it does not explicitly mention when not to use it or name alternative tools; the context is sufficient for this simple listing tool.

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