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generate_video

Create Seedance videos from text, images, or reference media, with cost checked by spend guard before generation.

Instructions

Make a Seedance video (text-to-video, image-to-video, or with reference media). Priced and checked by the spend guard before anything is sent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
waitNoBlock until the video is done
modelNo2.5 (best), 2.0, fast, mini (cheap drafts) or a full id
ratioNoadaptive
promptYesWhat happens in the clip
save_toNoFile or folder to save the mp4
durationNoSeconds, 2-15
timeout_sNo
watermarkNo
last_frameNoImage URL or local path
resolutionNo720p
approval_idNoOnly after the user said yes, or from a batch
first_frameNoImage URL or local path
camera_fixedNo
generate_audioNo
reference_audioNoAudio URLs
reference_imagesNoImage URLs or local paths
reference_videosNoPublic video URLs, e.g. an earlier video_url
return_last_frameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It does disclose one valuable trait — pricing and spend-guard gating happen before dispatch — but is silent on async vs blocking behavior, how 'wait' interacts with 'timeout_s', and the approval_id workflow, all of which matter for a 19-parameter generation call.

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?

Two sentences, front-loaded with the action and the key operational guarantee, with zero filler. It is arguably sparse for a 19-parameter tool, but every sentence earns its place.

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

Completeness2/5

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

An output schema exists, so return values need no explanation. However, for a 19-parameter mutation-style tool with no annotations, the description omits the async/blocking model, the approval flow implied by approval_id, and cost/approval prerequisites — too much is left for the agent to guess.

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 coverage is 58%, so the schema already documents many parameters. The description adds real value by mapping first_frame/last_frame/reference_images/reference_videos onto the text-to-video, image-to-video, and reference-media modes, but it does not compensate for the undocumented remainder.

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 ('Make a Seedance video') and enumerates the three generation modes, which maps directly to the first_frame/last_frame/reference_* parameters. It does not explicitly distinguish itself from siblings like video_task or generate_image, so it stops short of a 5.

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?

No when-to-use, when-not-to-use, or alternative routing is given. The mention of the spend guard hints at an approval workflow, but the agent is never told when to prefer video_task, cancel_video_task, or preapprove_spend, nor when this tool is the wrong choice.

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