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aeo_seo_research_generate_research_action

Discover keyword opportunities, AI citation gaps, competitor insights, and content recommendations by generating complete AEO & SEO research for any topic.

Instructions

Generates comprehensive AEO & SEO research for a given topic, including keyword opportunities, AI citation gaps, competitor landscape, and content recommendations.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "<topic>",
      "output_variable_name": "<output_variable_name>"
    },
    "name": "aeo_seo_research_generate_research_action"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicYes
research_depthNostandard
website_urlNo
optimization_focusNobalanced
output_variable_nameYesVariable name for the result.seo_research

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions generating research and lists included aspects, but does not disclose side effects, auth requirements, or output structure. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence that is front-loaded with the purpose and includes a list of outputs. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, low schema coverage, no output schema, and no annotations, the description lacks guidance on parameter usage, output format, and when to use sibling tools. Insufficient for a complex research tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (output_variable_name has a description). The description does not explain any parameters beyond the topic, leaving research_depth, website_url, and optimization_focus unexplained. Fails to compensate for low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it generates comprehensive AEO & SEO research for a topic, listing inclusions like keyword opportunities and competitor landscape. It distinguishes from siblings like industry_research_generate_research_action by specifying AEO & SEO focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage for AEO & SEO research tasks, but no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned despite sibling tools with similar names.

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

Deploy Server

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