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convert video to hdr

convert_video_to_hdr
Destructive

Convert an existing video to HDR using a catalog model that supports video_hdr. Select output format in modelSettings when supported. Use get_model_catalog to choose a supported model and its settings. Returns a tracked task and playable result when complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesActive model ID supporting this operation. Use get_model_catalog.
promptNoEdit or enhancement instructions.
maxCostUsdNoMaximum charge for each output. Checked against authoritative pricing before generation.
resolutionNo
aspectRatioNo
endFrameUrlNo
mediaInputsNoNamed media slots from get_model_catalog, for example reference_image_uri or mask_url.
scaleFactorNoUpscaling multiplier when supported by the selected model.
sparkTaskIdNoOriginating Spark task for library history and recovery.
workspaceIdNo
outputFormatNoOutput format when supported by the selected model.
generateAudioNoExplicitly enable or disable generated video audio, when supported.
modelSettingsNoModel-specific controls using keys and options from get_model_catalog inputConstraints.slots.
sourceMediaIdYesCompleted workspace source media. The original is preserved.
idempotencyKeyNoStable request key. Retries with the same key reuse the existing output and do not start another paid generation.
sourceImageUrlNoPublic HTTP(S) source image/start-frame URL. Use mediaId for workspace images.
sourceVideoUrlNoPublic HTTP(S) source-video URL.
endFrameMediaIdNoWorkspace image for the final frame, when supported by the selected model.
referenceImagesNoImages to guide generation. Use labels such as person or product and refer to them as @person or @product in the prompt. Each item accepts a workspace mediaId or a public HTTP(S) URL.
sourceImageMediaIdNoWorkspace image to use as the source image/start frame.
sourceVideoMediaIdNoWorkspace video to edit or transform, when supported by the selected model.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
errorNo
successYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this is a non-readOnly, openWorld, non-idempotent, destructive operation, and the description adds that it returns a tracked task with a playable result when complete. It does not warn that this is a paid generation, nor mention cost capping or idempotency-key behavior despite the tool being destructive and expensive. With annotations carrying the safety profile, this is a reasonable 3.

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?

Three short sentences, front-loaded with the conversion action and the model prerequisite, with no filler. It is slightly terse given the tool's complexity, but nothing wastes space.

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?

An output schema exists so return values need not be explained, and the schema covers most parameters, so the description is adequate for invocation. However, for a 21-parameter, destructive, paid generation tool, it omits cost/idempotency guidance and makes no attempt to orient the agent among the many video-mutation siblings.

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 81%, so the schema already documents most parameters and the baseline is 3. The description adds only marginal meaning by pointing at modelSettings for output-format selection; it says nothing about prompt, mediaInputs, idempotencyKey, maxCostUsd, or referenceImages semantics beyond what the schema already provides.

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?

The description states a specific verb+resource ('Convert an existing video to HDR') and adds a real constraint (the catalog model must support video_hdr). It does not explicitly contrast with near-neighbors such as enhance_video_media or edit_video, so an agent must still infer the boundary, but the HDR specificity is strong enough to identify the tool.

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?

It gives an actionable prerequisite: 'Use get_model_catalog to choose a supported model and its settings,' which routes the agent to the sibling needed before calling. There is no explicit when-not guidance or comparison to the other video-mutating siblings, so it falls short of a 5.

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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