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TeamDay-AI

SE Ranking MCP Server

by TeamDay-AI

AI Search: Get Prompts by Brand (SE Ranking)

DATA_getAiPromptsByBrand

Retrieve AI search prompts mentioning a brand to track brand visibility across LLMs. Filter by engine, region, volume, and keywords.

Instructions

Data Tool: Retrieves a list of prompts where the specified brand is mentioned in AI search results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoThe field to sort the results by. Options: volume, type, snippet_length.volume
brandYesBrand name to search for in LLM snippets.
limitNoMax prompts per page (1–1000). Default: 100.
engineYesLLM to query (e.g., 'ai-overview', 'chatgpt', 'perplexity', 'gemini', 'ai-mode').
offsetNoStarting index for pagination. Default: 0.
sourceYesAlpha-2 country code of the regional prompt database (e.g., 'us').
sort_orderNoSort direction. Default: desc.desc
filter_volume_toNoSpecifies the maximum volume of searches to be included in the results.
filter_volume_fromNoSpecifies the minimum volume of searches to be included in the results.
filter_keyword_count_toNoSpecifies the maximum number of words in prompts.
filter_keyword_count_fromNoSpecifies the minimum number of words in prompts.
filter_characters_count_toNoSpecifies the maximum prompt length in characters.
filter_characters_count_fromNoSpecifies the minimum prompt length in characters.
filter_multi_keyword_excludedNoA URL-encoded JSON string specifying keywords that must NOT be present in the prompt. For example: filter[multi_keyword_excluded]=[[{"type":"contains","value":"seo"},{"type":"contains","value":"tools"}],[{"type":"contains","value":"backlinks"}]]
filter_multi_keyword_includedNoA URL-encoded JSON string specifying keywords that must be present in the prompt. For example: filter[multi_keyword_included]=[[{"type":"contains","value":"seo"},{"type":"contains","value":"tools"}],[{"type":"contains","value":"backlinks"}]]
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It only states retrieval, but fails to mention pagination behavior, rate limits, authentication needs, or data source characteristics. This is insufficient for a tool with 15 parameters and high complexity.

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?

The description is a single, clear sentence without unnecessary words. It is appropriately sized but could be slightly improved with additional context without becoming verbose.

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 the 15 parameters, no output schema, and no annotations, the description is too minimal. It does not explain typical use cases, how filters interact, or what the response structure looks like. The complex filter parameters (e.g., filter_multi_keyword_included) lack any contextual guidance in the description.

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?

The input schema has 100% description coverage, so each parameter is already explained. The tool description does not add any additional meaning beyond what the schema provides. Baseline is 3 since schema covers parameters well.

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?

The description clearly states the tool retrieves prompts where a specified brand is mentioned in AI search results. It uses a specific verb ('Retrieves') and resource ('list of prompts'), and the brand parameter distinguishes it from the sibling DATA_getAiPromptsByTarget.

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

Usage Guidelines2/5

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, such as DATA_getAiPromptsByTarget. The description does not specify prerequisites, data freshness, or when not to use it. Usage is only implied by the purpose.

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

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