grok_list_models

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

No annotations are provided, so the description carries full burden. It specifies that it returns tables with capabilities, which is transparent but could mention if it makes a network call or requires authentication. For a simple read operation, this is adequate.

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 four sentences, well-structured with a summary, details on what it shows, and a return note. No fluff, every sentence adds value.

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 no parameters and an output schema, the description covers purpose, usage, and return format. It is complete for a list tool with siblings, and does not need to explain return values due to the output schema.

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?

There are no parameters, so schema coverage is 100% trivial. The description adds context about what the tool returns (chat + video models, capabilities), which is valuable beyond the empty schema. Baseline 4 for zero params 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 clearly states it lists all available Grok models (chat + video) and their capabilities, using a specific verb ('list') and resource ('models'). It distinguishes from siblings like grok_chat_completions (which uses models) and the video generation 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 explicitly says 'Use this to understand which model to choose,' providing clear usage guidance. While it doesn't mention when not to use or alternatives, the context is sufficient for a list tool.

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