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Generate Media

generate_media

Generate one first-class Library media item from a prompt. Choose generator: text-to-video | text-to-image | image-to-video | text-to-music | text-to-speech | text-to-sfx | auto. Put supported presentation controls in body.style and first/last/image references in body.refs. Returns { id, status:"generating", estimateUsd? }; returns 402 if the estimate exceeds the per-call ceiling. Async — call wait_job(kind="media", id=mediaItemId) or use a webhook (media.completed — status rides the payload). Use the returned id like any other media item.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesPOST /media/generate body.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
statusNo
estimateUsdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the async lifecycle, the exact success payload ({ id, status:"generating", estimateUsd? }), the 402 cost-ceiling failure mode, and the webhook event name. Annotations (readOnly=false, idempotent=false, destructive=false, openWorld=false) are consistent with, and supplemented by, this operational detail.

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?

Front-loads purpose, then generator list, parameter placement, return/error contract, and async handling in that order. Dense but every clause carries information; the generator enumeration is slightly list-heavy but justified by the enum's importance.

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?

For an async, nested-body, cost-sensitive generation tool, the description covers input shape, success and failure returns, completion paths, and downstream usage of the id. Nothing needed to invoke or follow up on the call is missing.

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 description coverage is 100% and the style sub-schema already documents aspect/durationSec/voice/speed/stability, so the description largely reinforces rather than adds. It does however clarify field placement (presentation controls in body.style, frame/image references in body.refs) and enumerates the generator values, which is useful orientation at the top level.

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 ('Generate one first-class Library media item from a prompt') and enumerates the generator modes, which cleanly separates it from sibling tools like import_media, prepare_media, and extract_media. An agent can tell what this produces and how it differs from adjacent media tools.

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

Usage Guidelines4/5

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

Gives clear routing guidance for the generator choice and, importantly, two completion paths (wait_job(kind="media", id=mediaItemId) or the media.completed webhook). It does not explicitly contrast when to use this versus import_media or prepare_media, so it stops short of full when/when-not coverage.

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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