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by com.productclank
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Check an AI creator's bio code

verify_ai_creator
Idempotent

Check that the listing's verify_code is in the AI creator's bio. X bios are read now and the listing is marked verified; TikTok, Instagram and YouTube are checked by hand in review (method: "manual"). Only the user's own listings. Free.

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": {
      "listing_id": "<listing_id>"
    },
    "name": "verify_ai_creator"
  }
}

Input Schema

NameRequiredDescriptionDefault
listing_idYeslisting_id from apply_ai_creator or get_ai_creator_status.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that X bios are read and the listing is marked verified, while TikTok, Instagram and YouTube go to manual review with `method: "manual"`. It also adds ownership and cost constraints, which meaningfully clarify the side effects and external checks.

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 front-loaded with the core action and then compactly covers platform differences, ownership, and cost in three sentences. There is no filler or redundant restatement.

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?

For a one-parameter verification tool with no output schema, the description gives the key outcome and platform-specific review path. It could say more about the response or what happens when the code is missing, but it is largely complete.

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 single `listing_id` parameter is documented as coming from `apply_ai_creator` or `get_ai_creator_status`. The description itself does not add further meaning or syntax for `listing_id`, so the baseline score applies.

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?

The description states a specific verb and resource: checking that the listing's `verify_code` appears in the AI creator's bio, and it describes the resulting verification outcome. It is clear, but it does not explicitly contrast this action with the sibling `get_ai_creator_status`, so it falls short of full sibling differentiation.

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 description supplies usage constraints such as 'Only the user's own listings' and 'Free', plus platform-specific review behavior, but it does not explicitly say when to choose this tool over alternatives like `get_ai_creator_status`. Usage is implied by the action itself rather than clearly routed.

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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