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upscale_video

Upscale a video from a public URL using Topaz AI. Creates a processing task, returns a task ID, status, and output URLs, with optional polling or webhook callback.

Instructions

Create a Topaz task on RunAPI (upscale video). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
timeout_msNo
callback_urlNoWebhook URL for terminal Task delivery.
upscale_factorNoVideo upscale multiplier.
poll_interval_msNo
source_video_urlYesPublic source video URL.
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the return value (task id, status, output URLs) but omits critical traits like asynchronous execution, polling/callback behavior, pricing implications, or any side effects. It does not disclose whether the task runs synchronously or how the video is processed.

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?

The description is a single, efficient sentence that front-loads the core purpose and return information. Every word contributes to understanding the tool's function without unnecessary filler. It earns its place by being concise and factual.

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?

This is a complex asynchronous tool with 7 parameters, no annotations, and no output schema, yet the description only covers basic creation and return. It omits usage context, distinction from upscale_image, and behavioral semantics like polling or webhooks. The description is inadequate for an agent to fully understand the tool's workflow and prerequisites.

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 71%, with descriptions for source_video_url, model, callback_url, upscale_factor, and additionalProperties. The description adds no parameter-level details, and the undocumented parameters (wait, timeout_ms, poll_interval_ms) remain unexplained by both schema and description. Since the schema covers most parameters, the baseline is acceptable, but no extra value is provided.

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 clearly states the action (create a Topaz task) and the domain (upscale video on RunAPI). It distinguishes from the sibling upscale_image by explicitly mentioning video. However, it doesn't explicitly say 'upscales a video file' as the primary purpose, relying on the parenthetical and tool name.

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 guidance is provided on when to use this tool versus alternatives like upscale_image. There are no exclusions, prerequisites, or context about whether to choose this over the image variant. The description only states what it does, not when it should be chosen.

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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