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

With no annotations, the description carries the full burden and does well: it discloses that the tool dispatches to AI workers (Modal), that credits vary by model/file size, that Day Pass and welcome credits do not include AI Studio, that files are deleted after processing, and that tasks are auditable. It also clarifies workspace unlock policies, adding useful behavioral context beyond the core function.

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 core purpose is front-loaded in the first sentence, but the description includes multiple sentences about credits, day passes, workspace subscriptions, and pricing links, which are tangential to tool invocation. While some of this context is useful, it is not as concise as it could be.

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?

Given the absence of an input schema, output schema, and annotations, the description provides essential context on usage, cost, data deletion, and auditability. However, it does not specify input formats, file size limits, output details, or whether processing is synchronous/asynchronous, leaving gaps for an agent that needs to invoke the tool correctly.

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?

The input schema is empty, but the description adds meaning by stating that a face photo and audio are the required inputs for creating a talking video. This gives the agent semantic understanding of what the tool operates on, exceeding the minimal baseline for zero-parameter tools.

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 opens with a specific verb+resource: 'Animate a face photo with audio to create a talking video.' This precisely states what the tool does and clearly distinguishes it from siblings like mio_ai_text_to_video or mio_ai_video_enhancer, which serve different purposes.

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 use case is implied through the description (animating a face photo with audio), but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The mention of AI Studio run and credits is more about account context than usage guidance.

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