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generate_video

Generate AI motion-capture or cinematic videos from a text prompt, with optional reference video for dance, runway, or motion transfer.

Instructions

Generate AI mocap or cinematic video from prompt or dance/runway reference.

Input Schema

NameRequiredDescriptionDefault
promptYesVisual action and scene description.
modelEngineNoVideo engine.seedance-2.5
durationSecondsNoVideo length in seconds.
referenceVideoUrlNoOptional motion transfer reference video URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
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 says nothing about credit consumption, expected generation latency, async job/polling behavior, or whether reference-based generation requires a specific model engine — all critical for a costly video-generation call. Only the existence of two generation modes is disclosed.

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?

A single front-loaded sentence with no filler; the verb and modes come first. It is efficient, though the compactness contributes to the missing usage and behavioral detail rather than offsetting it.

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?

For a 4-parameter creation tool with no annotations and no output schema, the description should at least indicate what comes back (job id, URL) and that generation is likely costly/asynchronous. It covers the core capability but leaves the agent under-informed about post-call behavior.

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%, so the schema already documents prompt, modelEngine, durationSeconds, and referenceVideoUrl. The description adds only a light hint that the reference input maps to dance/runway motion transfer, which is marginal value beyond the schema's own 'motion transfer reference video URL' text.

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?

States a specific verb and resource ('Generate ... video') and names two distinct output modes (AI mocap vs cinematic) plus two input paths (prompt or dance/runway reference). It does not explicitly differentiate itself from the nearest sibling, combine_videos, leaving a small ambiguity about which tool to pick for video work.

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

Usage Guidelines2/5

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

The description gives no when-to-use or when-not-to-use guidance, no prerequisites, and names no alternatives. An agent must infer that referenceVideoUrl implies motion transfer and that combine_videos is the tool for stitching existing clips.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.