Grok MCP

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

Annotations declare readOnlyHint=true, and the description aligns by describing a listing operation without contradictions. It adds valuable behavioral context beyond annotations by specifying the return format (Markdown sections with pricing and release dates) and the data source (xAI API), which helps the agent understand output structure and external dependencies.

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 front-loaded with the core purpose in the first sentence, followed by specific return details. Every sentence earns its place by clarifying output format and content without redundancy, making it efficient and well-structured.

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 (0 parameters, read-only), the description is complete. It explains what the tool does, the return format, and data sources, compensating for the lack of an output schema. No additional information is needed for effective agent use.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately adds no parameter details, as none are needed, and instead focuses on output semantics, which is relevant given the lack of an output schema.

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 specific action ('List all Grok language and image models'), identifies the resource (models from xAI API), and distinguishes this from siblings by specifying it returns models with pricing information, unlike other tools that focus on chat, files, or code execution.

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 implies usage context by mentioning 'live pricing' and model types, suggesting it's for informational purposes. However, it doesn't explicitly state when to use this tool versus alternatives like list_files or list_chat_sessions, nor does it provide exclusions or prerequisites for usage.

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