DataForSEO MCP Server

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

No annotations are provided, so the description carries full burden but fails to disclose key behavioral traits. It does not mention whether this is a read-only operation, potential rate limits, authentication needs, or what the output entails (e.g., audit results, scores, errors). The description only provides background on Lighthouse without operational details.

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 a single, well-structured sentence that efficiently explains the tool's basis without unnecessary details. It is front-loaded with the core information, though it could be more concise by directly stating the tool's function rather than background.

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 annotations and no output schema, the description is incomplete for a tool with 4 parameters and likely complex behavior (web page quality measurement). It lacks details on what the tool returns, error handling, or performance implications, leaving significant gaps for an AI agent to understand its 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?

Schema description coverage is 100%, so the schema fully documents all parameters (url, enable_javascript, custom_user_agent, accept_language). The description adds no additional meaning about parameters beyond what the schema provides, such as default behaviors or usage examples. Baseline 3 is appropriate given high schema coverage.

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 states the tool is 'based on Google's open-source Lighthouse project for measuring the quality of web pages and web apps,' which provides a general purpose but lacks specificity about what it actually does (e.g., run audits, generate reports, return scores). It distinguishes from some siblings like 'on_page_content_parsing' by mentioning Lighthouse, but the verb 'measuring' is vague compared to more precise alternatives.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention sibling tools like 'on_page_content_parsing' or 'on_page_instant_pages' for comparison, nor does it specify contexts or exclusions for usage. The description only gives background without practical application advice.

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