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Search AI answers

search_responses
Read-only

Read real AI answers collected for the brand: excerpts around the brand mention, whether the brand and which competitors were named, and the cited URLs. Filter by a word in the question or answer (query), by prompt text, and by engine.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_responses"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD. Default: now.
fromNoStart date YYYY-MM-DD. Default: all time.
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.
limitNoMax items to return (default 10, max 50).
queryNoOptional text to search in the question or the answer.
engineNoOptional AI engine filter, comma separated: chatgpt, gemini, perplexity, ai_overviews, ai_mode. Default: all engines.
offsetNoItems to skip, for pagination.
promptNoOptional text the tracked prompt must contain.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description adds genuinely new context with no output schema present: it discloses the shape of returned records (excerpts around the mention, naming of brand and competitors, cited URLs) and that all filters are optional.

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?

Two sentences with no filler; the return-payload summary is front-loaded before the filter sentence. The second sentence is a dense list that could be tightened slightly, but nothing is wasted.

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 correctly compensates by describing the returned fields, and it covers the three filtering dimensions. Minor omissions remain — pagination behavior and the default-brand fallback are left to the schema — but nothing an agent needs to call it correctly is absent.

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 description coverage is 100%, so all eight parameters (including the comma-separated engine list and pagination fields) are already fully documented. The description names query, prompt, and engine but adds no format or syntax detail beyond what the schema provides, so the baseline of 3 applies.

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?

States a specific verb and resource ('Read real AI answers collected for the brand') and then enumerates the payload (brand-mention excerpts, brand/competitor naming, cited URLs). This payload description distinguishes it from siblings like get_top_sources or get_visibility, which cover only sources or metrics.

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?

The second sentence describes the available filters (query, prompt, engine), which implies how to narrow results, but never states when to choose this tool over get_top_sources or get_visibility, nor any prerequisites or exclusions. Usage is inferable from the filter list rather than spelled out.

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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