grok_codex_list_models

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

No annotations are provided, so the description must fully convey behavioral traits. It only states the basic function without disclosing side effects, authentication needs, rate limits, or whether the operation is read-only. For a listing tool, this is minimal disclosure.

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 a single concise sentence that front-loads the tool's purpose. No extraneous information is included, and every word 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?

Given the tool's simplicity (one parameter, no output schema), the description covers the primary purpose and hints at parameter usage. However, it lacks details about the output format (e.g., what fields are returned for each model) and does not confirm whether the operation is read-only. These gaps reduce completeness.

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 schema has 0% description coverage, so the description must compensate. It hints that the 'probe' parameter may relate to 'live models', but does not explicitly map the parameter name to its effect. This adds some meaning but leaves ambiguity about the parameter's exact semantics.

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 the tool's function: 'List curated (and optionally live) models.' It uses a specific verb ('list') and resource ('models'), and distinguishes between two types of models. Sibling tools are unrelated to listing models, so there is no ambiguity.

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 a hint about when to use the probe parameter ('optionally live models'), but does not offer explicit guidance on when to use this tool versus alternatives, nor does it specify when not to use it. Since siblings are all distinct, usage context is implied but not fully articulated.

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