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GenMagic

by io.github.yumaheymans
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Create a video

create_video

Start generating a video from a text description with GenMagic, with any text-to-video model, clip length, resolution and sound the model supports (list_models with category "video" shows them and the per-second price). Video is asynchronous, so this returns a job id immediately (nothing is charged yet). Poll it with the get_video tool every few seconds until the status is "completed" to get the hosted video URL. A failed render is never charged. On-brand automatically when the account has brand personalization on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional GenMagic model id for the video (call list_models with category "video" for the ids and prices). Omit it to let GenMagic choose its default.
promptYesA description of the video to create.
durationNoClip length in seconds, one of the lengths the model supports (list_models shows durations_seconds). Omit for the model's default.
resolutionNoOutput resolution the model supports, e.g. 720p or 1080p (list_models shows resolutions). Omit for the model's default.
aspect_ratioNoAspect ratio: 16:9 (landscape), 9:16 (portrait), or 1:1 (square). Defaults to 16:9.
generate_audioNoGenerate sound with the clip on models that support it (list_models shows audio_supported). Omit for the model's default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / duration
      Added value: +{
+  "description": "Clip length in seconds, one of the lengths the model supports (list_models shows durations_seconds). Omit for the model's default.",
+  "type": "integer"
+}
    • addedInput schema / properties / generate_audio
      Added value: +{
+  "description": "Generate sound with the clip on models that support it (list_models shows audio_supported). Omit for the model's default.",
+  "type": "boolean"
+}
    • addedInput schema / properties / model
      Added value: +{
+  "description": "Optional GenMagic model id for the video (call list_models with category \"video\" for the ids and prices). Omit it to let GenMagic choose its default.",
+  "type": "string"
+}
    • addedInput schema / properties / resolution
      Added value: +{
+  "description": "Output resolution the model supports, e.g. 720p or 1080p (list_models shows resolutions). Omit for the model's default.",
+  "type": "string"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses that the call is asynchronous, returns a job id immediately, charges nothing at kickoff, never charges a failed render, and that polling is required to obtain the hosted video URL. It also notes brand personalization is applied automatically when the account has it enabled.

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?

Four tightly packed sentences, front-loaded with the action first, then async behavior, next step, and billing semantics in descending order of importance. No sentence is filler; the discovery hint and pricing note both serve the caller.

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?

There is no output schema and no annotations, so the description must explain the return path, and it does: a job id now, hosted URL via get_video polling. Billing behavior and the optional brand personalization are also covered, leaving no material gap for a 6-parameter async generation tool.

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 100%, so each parameter is already fully documented in the schema, including the pointers to list_models for model ids, durations_seconds, resolutions and audio_supported. The description mostly restates the same model-support constraints, adding only the per-second pricing hint; baseline 3 is appropriate.

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 generating a video from a text description with GenMagic") and immediately scopes it to text-to-video models, clearly distinguishing it from sibling generators like generate_image, generate_music, generate_speech and generate_text. It also separates itself from get_video by framing this tool as the creator that returns a job id.

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?

Explicitly routes the agent to the companion tools: list_models with category "video" to discover models and prices, and get_video for polling "every few seconds until the status is 'completed'." The when-to-use context (asynchronous text-to-video generation) is stated with no inference required.

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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