generate_video_from_video

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the AI transformation nature and model capabilities (Lucy for restyling, Kling for motion control), which adds useful context beyond what parameters indicate. However, it doesn't describe important behavioral aspects like processing time, rate limits, authentication requirements, output format, or error conditions that would be crucial for an agent to use this tool effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise and front-loaded: two sentences that immediately convey the core functionality and a critical prerequisite. Every word earns its place - the first sentence defines the tool's purpose and capabilities, the second provides essential usage guidance. No wasted words or redundant information.

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

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

For a complex tool with 14 parameters, no annotations, and no output schema, the description provides adequate but incomplete context. It covers the high-level purpose and a critical prerequisite (upload_file for local videos), but doesn't address output format, error handling, performance characteristics, or integration patterns that would help an agent use this tool effectively in broader workflows.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 14 parameters thoroughly with descriptions, defaults, enums, and constraints. The description adds minimal parameter semantics beyond the schema - it only mentions the two main capabilities (restyling and motion transfer) that map to the 'model' parameter options. This meets the baseline of 3 when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Transform an existing video using AI' with specific capabilities mentioned (restyling with Lucy models, motion transfer with Kling motion control). It distinguishes from sibling tools like 'generate_video' or 'generate_video_from_image' by specifying it works from an existing video source. However, it doesn't explicitly contrast with all possible siblings like 'edit_image' or 'inpaint_image'.

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

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

The description provides clear usage context: 'Use upload_file first if you have a local video' gives practical guidance for handling local files. It implies when to use this tool (for video-to-video transformations) versus alternatives like 'generate_video' (from scratch) or 'generate_video_from_image' (from images). However, it doesn't explicitly state when NOT to use this tool or name specific alternative tools for different scenarios.

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