model_settings_lookup

What is model_settings_lookup?

model_settings_lookup is a paid work product in the Gen-Video Intel category on agenttoll.dev. It costs $0.02 per call, settled in USDC on Base via the x402 payment protocol. No API keys or accounts: your agent inspects the metadata, explains the expected result, caps the spend, calls the tool, and receives structured JSON with a receipt envelope.

Input parameters

Only send these request-body fields. If this block is empty, send {}.

{
  "model": "string model family e.g. wan, vace, ltx, flux3, seedance, kling, hunyuan, qwen-image",
  "task": "optional task e.g. image-to-video, face consistency, LoRA training, fp8, ComfyUI workflow"
}

Request body

{
  "model": "wan",
  "task": "face consistency settings"
}

HTTP endpoint

POST JSON to this URL. The first unpaid call returns HTTP 402 with x402 payment requirements; an x402-capable client signs and retries.

https://agenttoll.dev/paid/media/model-settings

MCP call

Connect an MCP client to the endpoint, call tool model_settings_lookup, and pass the request body as arguments.

https://agenttoll.dev/mcp

MCP paid-tool calls may surface the payment challenge inside the JSON-RPC result instead of as a raw HTTP 402.

What the agent needs to transact

{
  "mcp": {
    "endpoint": "https://agenttoll.dev/mcp",
    "tool": "model_settings_lookup",
    "arguments": {
      "model": "wan",
      "task": "face consistency settings"
    }
  },
  "http": {
    "method": "POST",
    "url": "https://agenttoll.dev/paid/media/model-settings",
    "headers": {
      "content-type": "application/json"
    },
    "body": {
      "model": "wan",
      "task": "face consistency settings"
    },
    "unpaid_response": "HTTP 402 with x402 payment requirements",
    "paid_response": "HTTP 200 JSON with payment-response receipt header"
  },
  "payment": {
    "protocol": "x402",
    "scheme": "exact",
    "price_usd": "0.02",
    "max_payment_usd": "0.02",
    "network": "eip155:8453",
    "network_name": "Base mainnet",
    "asset": "USDC",
    "asset_address": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "pay_to": "0x62a0D3d9DF0dE8804983009949c714EaeAFd87F1"
  },
  "expected_result": "JSON with scored settings discussions for video/image models, including CFG, steps, denoise, fps, resolution, LoRA/training and ComfyUI notes where found.",
  "approval_prompt": "This AgentToll call costs $0.02 on Base mainnet. Verify payTo 0x62a0D3d9DF0dE8804983009949c714EaeAFd87F1, asset 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913, and maxPayment $0.02 before approving. It returns JSON with scored settings discussions for video/image models, including CFG, steps, denoise, fps, resolution, LoRA/training and ComfyUI notes where found.",
  "receipt": "https://agenttoll.dev/receipt/:tx",
  "receipt_schema": "https://agenttoll.dev/agenttoll-receipt-v1.md"
}

Agent approval metadata

Use this before asking a user to approve payment. It states the cap, seller wallet, asset, route, and expected result in one buyer contract.

Suggested approval line: This AgentToll call costs $0.02 on Base mainnet. Verify payTo 0x62a0D3d9DF0dE8804983009949c714EaeAFd87F1, asset 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913, and maxPayment $0.02 before approving. It returns JSON with scored settings discussions for video/image models, including CFG, steps, denoise, fps, resolution, LoRA/training and ComfyUI notes where found.

{
  "schemaVersion": "agenttoll.buyer_contract.v1",
  "service": "agenttoll.dev",
  "tool": "model_settings_lookup",
  "category": "Gen-Video Intel",
  "method": "POST",
  "endpoint": "https://agenttoll.dev/paid/media/model-settings",
  "priceUsd": "0.02",
  "maxPaymentUsd": "0.02",
  "protocol": "x402",
  "scheme": "exact",
  "network": "eip155:8453",
  "networkName": "Base mainnet",
  "asset": "USDC",
  "assetContract": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
  "payTo": "0x62a0D3d9DF0dE8804983009949c714EaeAFd87F1",
  "facilitator": "https://api.cdp.coinbase.com/platform/v2/x402",
  "requestBody": {
    "model": "wan",
    "task": "face consistency settings"
  },
  "input": {
    "model": "string model family e.g. wan, vace, ltx, flux3, seedance, kling, hunyuan, qwen-image",
    "task": "optional task e.g. image-to-video, face consistency, LoRA training, fp8, ComfyUI workflow"
  },
  "expectedResult": "JSON with scored settings discussions for video/image models, including CFG, steps, denoise, fps, resolution, LoRA/training and ComfyUI notes where found.",
  "verifyBeforePaying": [
    "network must equal eip155:8453",
    "asset contract must equal 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "payTo must equal 0x62a0D3d9DF0dE8804983009949c714EaeAFd87F1",
    "maxPayment must be no more than $0.02",
    "resource path must match this endpoint"
  ],
  "receiptSchema": "https://agenttoll.dev/agenttoll-receipt-v1.md"
}

Pricing & payment

Paid JSON responses include agenttoll_receipt with request, result, and payment-term hashes. The receipt lets a user audit what the agent bought after the call. If your buyer runtime exposes a settlement transaction hash, verify it at /receipt/<tx>.

FAQ