cfp-seo-agent

ai_keyword_demand

Idempotent

Estimate modeled AI-search demand for up to 10 keywords with 12-month history. Use the JSON output as a relative demand indicator, not a measured prompt count.

Instructions

Modeled (estimated) AI-search demand for up to 10 keywords with 12-month history (DataForSEO AI Optimization Keyword Search Volume). Returns: JSON with estimate, source, methodology, keywords, not_found. SANDBOX (development): returns dummy data, no payment. NOTE: Modeled estimate, not a measured count. DataForSEO calculates AI search volume from statistical data on questions in Google's 'People Also Ask' results; it does not report actual prompt counts from any AI platform (ChatGPT, Gemini, Perplexity, ...). Use it as a relative demand indicator.

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": {
      "keywords": "<keywords>"
    },
    "name": "ai_keyword_demand"
  }
}

Input Schema

Name	Required	Description
`keywords`	Yes	Keywords to look up: 1 to 10 entries, each up to 80 characters / 10 words. Lowercased, duplicates removed.
`language_code`	No	Language code such as en or de. Default: English if available for the country, else its first language. Unsupported country/language pairs are refused before payment.
`location_code`	No	DataForSEO location code. Country level: 2840 = United States (default), 2276 = Germany, 2040 = Austria, 2756 = Switzerland. Google SERP, Maps, News, Images and Local Market Check also accept city/region codes in Germany, Austria and Switzerland (free lookup: GET /api/v1/locations?q=...).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 23, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Beyond the annotations (readOnlyHint=false, idempotent, openWorld), the description discloses the sandbox/dummy-data mode and that no payment is taken, plus the important limitation that DataForSEO derives volume from 'People Also Ask' statistics rather than real prompt counts. That is exactly the kind of operational context annotations cannot carry.

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

Conciseness4/5

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

Front-loaded with purpose, then return shape, then environment and limitation notes. The methodology sentence is long but earns its place by preventing misuse of the estimate; only mild redundancy in repeating the keyword cap.

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

Completeness4/5

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

With no output schema, the description lists the returned keys (estimate, source, methodology, keywords, not_found) and flags the cost/sandbox behavior. Minor gap: it doesn't explain the shape of the 12-month history or the unit of 'estimate', which an agent may need to interpret results.

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

Parameters3/5

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

Schema coverage is 100%, so keywords/language_code/location_code are already fully documented including defaults and location codes. The description only restates the 'up to 10 keywords' and '12-month history' bounds, adding no syntax or format detail beyond the schema.

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

Purpose4/5

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

States a specific verb+resource: modeled AI-search demand for up to 10 keywords with 12-month history, plus the upstream data source (DataForSEO AI Optimization Keyword Search Volume). It does not explicitly contrast with the nearby sibling keyword_metrics, so an agent must infer which of the two demand/keyword tools to pick.

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?

It gives a framing instruction ('Use it as a relative demand indicator') and a clear caveat that the number is modeled, not measured. However, there is no explicit when-to-use vs. keyword_metrics, keyword_ideas, or search_intent, and no statement of when this is the wrong tool.

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