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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description does add a genuinely useful behavioral fact that structured fields lack: it is usage-billed at roughly $0.012 per request. That cost disclosure is the only added value, and it is templated boilerplate rather than tool-specific behavior.

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 core sentence is short and front-loaded, but the appended pricing block with HTML-comment markers is template noise unrelated to tool selection. Roughly half the text does not earn its place for an agent deciding whether to call this tool.

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?

With no parameters, an output schema present, and rich annotations, the description does not need to explain returns or safety. Only the missing scoping context (which scraper's language set this is) keeps it from being fully complete.

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 zero parameters and 100% schema description coverage, so the baseline of 4 applies. Nothing in the description is needed to explain parameter usage.

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 says only that you 'will receive the list of languages,' which is a vague restatement of the tool name rather than a precise statement of what resource is returned and under what framing (e.g., languages supported by the Gemini LLM scraper). It does not distinguish this tool from the closely named sibling get_dataforseo_ai_gemini_llm_scraper_locations.

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?

There is no guidance on when to call this versus the many sibling lookup endpoints (scraper_locations, responses_models, llm_mentions_locales, etc.). The agent must infer usage entirely from the tool name.

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