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by ai.go-rocket
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Create a video ad from a website

create_video
Idempotent

Start a finished 9:16 AI User Generated Content (UGC) video ad for a website: a photoreal presenter speaks about the product, captions included, in the site's brand colours. Spends credits from the signed-in Go Rocket account (15 seconds, or 30 with cinema; get_account lists the credit costs) including comp credits, and starts at once. Signed out, connect your existing account with sign_in, then retry in the same chat. When credits are insufficient the reply carries plan_url: see the plan on go-rocket.ai. It can be cancelled with a full refund for 60 seconds. Returns a video_id right away; the video takes about 15 minutes, so poll get_video. Pass an idempotency_key when retrying so a repeated call returns the same video instead of paying twice. For a spoken business name without a URL, find its official website first and confirm the URL in one line before calling. Put the requested tone and audience in brief. Read back the returned message, then use status_tool to fetch the share_url when ready.

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": {
      "url": "<url>"
    },
    "name": "create_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesThe product or landing page to advertise, e.g. https://example.com/product
briefNoOptional tone, audience and focus, e.g. 'relaxed, for tourists, beginner surf lessons'.
qualityNoQuality tier (default 'standard', 1 credit per 15 s; 'cinema' is our most lifelike motion, 2 credits, up to 30 s).
languageNoSpoken language, ISO code (default en). One of the presenter languages listed by get_account.
presenterNoPresenter voice and face (default female).
length_secondsNoVideo length (default 15; 30 needs quality 'cinema').
idempotency_keyNoOptional but recommended for loops: any unique string per intended video.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / length_seconds / description
      Previous value: -"Video length (default 15)."New value: +"Video length (default 15; 30 needs quality 'cinema')."
    • changedInput schema / properties / length_seconds / enum
      Previous value: -[
-  15,
-  30,
-  60
-]New value: +[
+  15,
+  30
+]
    • addedInput schema / properties / quality
      Added value: +{
+  "description": "Quality tier (default 'standard', 1 credit per 15 s; 'cinema' is our most lifelike motion, 2 credits, up to 30 s).",
+  "enum": [
+    "standard",
+    "cinema"
+  ],
+  "type": "string"
+}
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: credits are spent immediately (including comp credits), the job is cancellable with a full refund for 60 seconds, rendering takes ~15 minutes, and a repeated call without an idempotency key can double-charge. This is exactly the kind of cost, latency and reversibility context annotations cannot convey.

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?

Dense but front-loaded: the capability and cost land in the first two sentences, then conditional paths. Every sentence is actionable, though the description is long enough that a reader must hold several branch conditions (auth, credits, no-URL, polling) at once.

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 no output schema, the description still explains the immediate return (video_id plus a message that may carry plan_url) and how to obtain share_url later. Combined with the credit, timing and cancellation details, an agent has everything needed to invoke and follow up correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already documented; the description still adds workflow meaning — what belongs in brief (tone and audience), the cinema↔30-second coupling, and why idempotency_key matters on retries. Marginal but genuine value on top of the schema.

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 — start a finished 9:16 AI UGC video ad from a website — plus the concrete output (photoreal presenter, captions, brand colours). It is clearly distinguishable from siblings like get_video_sample and get_sample_status, which retrieve samples rather than create a rendered ad.

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 routing for multiple situations: signed out → sign_in then retry in the same chat; insufficient credits → read plan_url; business name without URL → find and confirm the official site first; after creation → poll get_video / status_tool for share_url. It also names the retry discipline (idempotency_key) and the cancellation window.

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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