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AI visibility of one prompt

visibility__prompt
Read-onlyIdempotent

One tracked prompt in the latest scan: each engine's answer, the brands it names (with sentiment and quotes), the pages it cites, the sub-queries the engine searched (fan-out), and the stored "how to get cited" advice. Use it to see why a prompt is lost, which pages to get onto, and how buyers phrase the question.

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": {
      "workspace_id": "<workspace_id>",
      "prompt_id": "<prompt_id>"
    },
    "name": "visibility__prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
prompt_idYesFrom visibility__overview.
workspace_idYesFrom workspace__list.

Output Schema

NameRequiredDescriptionDefault
tagsNo
textYes
topicNo
adviceYessummary, article_keyword, scan_finished_at (the scan it was made for: it can be older than the answers), actions (title, detail, type, target). Null when none was made for this prompt.
intentNo
answersYesPer engine: model, status (answered|refused|error), answer (first 6000 chars), answer_truncated, own_cited, own_position, brands_analyzed (false while brands are still being read from it, so brands [] means not read yet), brands (brand, domain, sentiment, quotes), citations (url, domain, title), fan_out_queries.
prompt_idYes
workspace_idYes
scan_finished_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The annotations already declare read-only, idempotent, closed-world, and non-destructive behavior, so the description does not need to restate safety. It adds useful context beyond annotations by clarifying that results come from the latest scan and by listing the stored diagnostic content returned.

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?

The description is two sentences: the first front-loads the scope and payload, and the second provides actionable use cases. It is dense but every clause carries information, with no repetition of annotation or schema details.

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

Completeness5/5

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

With an output schema present and complete parameter descriptions, the description does not need to explain return structure, yet it usefully clarifies snapshot recency and the diagnostic purpose. For a read-only single-record lookup, nothing material is missing.

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%, and the schema already explains that prompt_id comes from visibility__overview and workspace_id from workspace__list. The description adds only the general notion of a tracked prompt and latest scan, not additional parameter semantics or usage constraints.

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 identifies the resource concretely: one tracked prompt in the latest scan, and enumerates the payload (engine answers, named brands with sentiment and quotes, cited pages, fan-out sub-queries, and stored citation advice). That single-prompt scope distinguishes it from the aggregate visibility__overview and source-focused visibility__sources.

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

Usage Guidelines4/5

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

The second sentence gives clear diagnostic use cases: seeing why a prompt is lost, which pages to target, and how buyers phrase the question. It does not explicitly name when to use visibility__overview instead, so it stops short of full when/when-not/alternative guidance.

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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