text_to_video

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

No annotations are provided, so the description carries the burden. It discloses that the model is local and that parameters have sensible defaults, but it does not mention execution behavior such as asynchronous processing, resource usage, or output delivery. The local vs cloud distinction is helpful but does not go far enough to fully disclose behavior.

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 two short sentences: the first states the core function, the second gives usage guidance. Every sentence adds value, and it is front-loaded.

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?

The description covers purpose, local vs cloud alternatives, and parameter optionality, but it does not explain whether the tool runs asynchronously or how the generated video is returned. Given the complexity of video generation and the presence of job management siblings, this is a notable gap. However, the output schema likely covers the return value.

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 documents all parameters. The description adds a general statement that all parameters except prompt are optional with defaults, but that is also already reflected in the schema (default values and required list). Thus no additional meaning beyond schema is provided.

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 explicitly states 'Generate a video from a text description using LTX-Video (local model)', which is a specific verb and resource. It also distinguishes from cloud alternatives by mentioning sora_video_generate() and run_api_node(), so it clearly differentiates from siblings.

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 gives explicit when-to-use vs alternatives: 'For cloud-based video generation, use sora_video_generate() or run_api_node() with Kling/Runway/Luma/etc.' It also tells the agent that all parameters except prompt are optional with defaults, providing customization guidance.

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