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 for behavioral disclosure. While it mentions the data sources, it doesn't address important behavioral aspects: whether this is a read-only operation, rate limits, authentication requirements, response format, pagination, or error conditions. For a tool with 9 parameters and no output schema, this leaves significant gaps in understanding how the tool behaves.

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 appropriately concise with two sentences that directly address the tool's function and scope. The first sentence states the core purpose, and the second provides additional context about available data sources. There's no wasted language or unnecessary elaboration.

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 the tool's complexity (9 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain what the tool returns, how to interpret the results, or provide context about Google Trends data limitations. For a data retrieval tool with multiple configuration options and no output schema, users need more guidance about expected outputs and result interpretation.

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 schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions the data sources (which relates to the 'type' parameter) but doesn't provide additional context about parameter interactions, dependencies, or best practices. The baseline of 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'provide you with the keyword popularity data from the 'Explore' feature of Google Trends.' It specifies the verb ('provide'), resource ('keyword popularity data'), and source ('Google Trends Explore feature'). However, it doesn't explicitly distinguish this tool from its sibling 'kw_data_google_trends_categories' or other keyword data tools, which would be needed for a perfect score.

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 mentions what data sources are available ('Google Search, Google News, Google Images, Google Shopping, and YouTube'), but provides no guidance on when to use this tool versus alternatives like 'kw_data_google_ads_search_volume' or 'kw_data_dfs_trends_explore'. There's no mention of prerequisites, limitations, or typical use cases for Google Trends data versus other keyword tools.

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