DataForSEO MCP Server

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

With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose if this is a read-only operation, whether it requires authentication, has rate limits, or what the output format might be (e.g., JSON list of filters). The phrase 'provides all the necessary information' is vague and doesn't add concrete behavioral context beyond a basic informational purpose.

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, clear sentence that efficiently states the tool's purpose without unnecessary words. It's front-loaded with the key information, though it could be slightly more structured by explicitly mentioning it's a metadata or reference tool. There's no waste, but minor improvements in specificity could elevate 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?

Given 0 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. It identifies the tool as informational about filters for a specific API set, but lacks details on output format, error handling, or integration with sibling tools. For a tool with no inputs, it's complete enough to understand the basic intent, but could better address behavioral aspects and usage context.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, avoiding redundancy. However, it could marginally improve by noting the lack of inputs, but this isn't required for a high score given the schema's completeness.

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 provides 'all the necessary information about filters that can be used with AI Optimization LLM Mentions API endpoints', which clarifies it's about filter information for a specific API category. However, it's somewhat vague about what 'information' entails (e.g., filter types, usage examples, or metadata) and doesn't explicitly differentiate from sibling tools like 'ai_optimization_llm_mentions_search' or 'ai_optimization_llm_mentions_aggregated_metrics', which might also involve filters.

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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing to know filter options before using search tools), exclusions, or compare it to similar tools like 'dataforseo_labs_available_filters' or 'domain_analytics_technologies_available_filters' in the sibling list, leaving the agent to infer usage context.

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