ask_grok

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

No annotations are provided, so the description bears full responsibility. It discloses that the tool supports system prompts and sampling parameters, but does not describe response format, rate limits, authentication needs, or any behavioral traits beyond the basic action.

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 three concise sentences with no wasted words. It front-loads the core purpose and efficiently lists supported parameters and additional guidance.

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 6 parameters, no output schema, and no annotations, the description is adequate but incomplete. It covers default model and parameter types, but lacks details on output format, error handling, or behavioral constraints for a chat tool.

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 baseline is 3. The description adds minimal extra meaning: it mentions the default model 'grok-4.3' and that system prompt is optional, but otherwise does not enhance understanding of temperature, max_tokens, or top_p beyond their schema descriptions.

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 asks Grok a question and gets a response, and mentions default model and supported parameters. However, it does not differentiate from siblings like grok_consensus or grok_validate, which limits clarity on when to use this specific tool.

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?

Usage is implied: ask a question and get a response. It suggests using list_models for model options, but provides no explicit guidance on when to use this tool versus alternatives like grok_consensus, nor any exclusion criteria.

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