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CreativeClaw

CreativeClaw

Official
by CreativeClawCo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

generate_video

Creates video content from a text prompt, supporting multiple models and flexible durations.

Instructions

Generate cinematic video content using state-of-the-art models including Gemini Omni, Veo, Sora, Kling, Seedance, MiniMax, and Hailuo. Supports text-to-video, image-to-video animation, reference-based generation, native audio, and multi-shot film production. Handles durations from 2-30+ seconds depending on model. Requires connection to the full Creative Claw MCP server.

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": {
      "prompt": "<prompt>"
    },
    "name": "generate_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesDescription of the video to generate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the requirement of a connection to the Creative Claw MCP server but does not disclose output format, asynchronous behavior, credits consumption, or other side effects. This leaves important behavioral aspects unclear.

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 concise and well-structured, front-loading the core purpose in the first sentence. It efficiently covers supported models, generation modes, duration range, and a connection requirement without unnecessary detail.

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

Completeness3/5

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

The description gives a good overview of capabilities and constraints but omits output details and workflow information. Given that a sibling tool check_job exists, the asynchronous nature is implied but not explained, leaving some context incomplete.

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?

The schema already describes the only parameter, prompt, as 'Description of the video to generate', giving full coverage. The tool description does not add extra parameter-level detail beyond this, so it meets the baseline but provides no additional clarification.

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 clearly states the tool's purpose: generating cinematic video content. It distinguishes itself from sibling tools like generate_image and generate_speech by focusing specifically on video and enumerating supported generation modes.

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 implies when to use the tool by mentioning video-specific capabilities, but it does not explicitly compare against alternatives or state when not to use it. There is no direct guidance for choosing between this and sibling tools such as generate_image or generate_speech.

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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