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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is a safe read operation. The description adds that the request is geo-targeted from a chosen country/state and returns cited sources, which is useful context beyond annotations. It does not disclose rate limits, cost considerations, or that responses are external AI answers, but given annotation coverage, 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 two sentences long with no waste, front-loading the core action and result. It packs the scope (chosen country/state, cited sources) and the usage motive (see brands/sources) efficiently. Slight deduction for not mentioning the includes or state/country dependency in the main description, but the schema covers it.

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?

The tool has 4 parameters but only 2 required, and the schema provides rich descriptions for all parameters including 'include' flags and state/country codes. The output schema does not exist, but the description states the return value (answer with cited sources). However, the description does not explain that the response might be large with include flags or that list_countries/list_states are needed for valid values, though these are in the schema. Overall, information is sufficient for an agent to call correctly, with minor gaps.

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%, and the schema already documents all parameters. The description adds the purpose of the country/state targeting (geo-targeting) and the cited-sources context, but it does not add much beyond schema descriptions. The description in the schema for 'include' already explains the flags, so the main description adds minimal extra parameter 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 specific verb (Submit), resource (prompt to Grok), and the key scoping feature (from a chosen country/state), and explicitly mentions returning answers with cited sources. It also differentiates from siblings by naming Grok explicitly and describing what it adds (cited sources/brands), distinguishing it from scrape_chatgpt, scrape_gemini, etc.

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 tells when to use the tool: to see how Grok answers a prompt and which brands/sources it mentions. It also implicitly routes to list_states and list_countries for valid codes, which provides context for prerequisites. However, it does not explicitly state when to prefer this over sibling tools (e.g., versus scrape_chatgpt), leaving some inference to the agent based on the tool name.

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