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Keytomic

by com.keytomic.app
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Start AI visibility setup

start_visibility_setup

Starts the AI Visibility setup of a site, the same as the AI Visibility page: Keytomic researches the site and saves the questions buyers ask AI as Suggested prompts. It saves only Suggested prompts: it makes no prompt Active and starts no check. Keytomic pays for the setup, so it uses nothing of the plan. A completed setup is used again, with no new research. It returns the setup status from before this start; follow the progress with get_visibility (the setup status of the overview section, and the suggestions section). When AI Visibility is off in this deployment, the call gives feature_disabled.

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>"
    },
    "name": "start_visibility_setup"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectIdYesSite to act on, from list_sites.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only flag it as non-read-only, open-world, non-idempotent and non-destructive; the description adds far more: only Suggested prompts are persisted, no plan quota is consumed, re-running against a completed setup performs no new research, and it returns the pre-start status rather than the new one.

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?

Roughly five short sentences, each carrying distinct information (scope, side effects, cost, reuse, return value, follow-up, error case) with the core behavior front-loaded and no filler.

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?

There is no output schema, yet the description explains that the returned status is the pre-start snapshot and that progress must be polled via get_visibility's overview and suggestions sections, covering both the async lifecycle and the failure mode.

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% and the single projectId parameter is already documented as the site from list_sites, so the description adds no parameter-level meaning. Baseline 3 applies when the schema carries the parameter semantics.

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 ('Starts the AI Visibility setup of a site') and explicitly distinguishes itself from the check flow by saying 'it makes no prompt Active and starts no check', which separates it from siblings like start_visibility_check.

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

Usage Guidelines5/5

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

Gives explicit when-to-use context (same as the AI Visibility page), what not to expect (no Active prompts, no check started, no plan usage), reuse behavior for completed setups, the follow-up tool (get_visibility with the overview and suggestions sections), and the feature_disabled branch when the feature is off.

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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