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Get an AI answer

get_ai_response
Read-only

Read the full text of one recorded AI answer.

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": {
      "projectId": "<projectId>",
      "siteId": "<siteId>",
      "runId": "<runId>"
    },
    "name": "get_ai_response"
  }
}

Input Schema

NameRequiredDescriptionDefault
runIdYes
siteIdYes
projectIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnly, non-destructive and closed-world, so the safety profile is covered. The description adds one useful behavioral fact — it returns the FULL TEXT of a single answer rather than a summary or list. It does not say what happens when the run is missing or how large the text may be, so it is adequate but thin.

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?

A single front-loaded sentence with no filler. It is efficient but so short that it omits information the schema does not supply, bordering on under-specification rather than waste.

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?

No output schema, three fully undocumented required parameters, and no explanation of how the answer text is keyed or bounded. The definition does not do enough for an agent to call this correctly without guessing at ID scoping.

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?

Three required parameters (projectId, siteId, runId) at 0% schema description coverage, and the description mentions none of them. 'One recorded AI answer' vaguely points at runId, but the required projectId/siteId scoping and their formats are left entirely undocumented by both schema and description.

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 and resource ('Read the full text of one recorded AI answer') and implies single-item retrieval, which separates it from list_ai_visibility_prompt_runs. It does not explicitly name which sibling produces the ID it consumes, so differentiation is implied rather than stated.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as list_ai_visibility_prompt_runs (to find the run) or get_ai_visibility_citations (for citation data). The agent must infer the retrieval workflow entirely.

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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