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

Annotations already mark the tool as read-only and idempotent. The description adds behavioral context by clarifying that it 'returns the styled prompt stack' rather than an image, and by suggesting it should be paired with generate_image. This goes beyond the annotation hints and helps set expectations for the output.

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 concise sentences with the purpose upfront, followed by concrete options and output behavior. Every sentence earns its place and there is no redundant repetition of schema details. It is well-structured and easy to scan.

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 simple 2-parameter, read-only style tool with no output schema, the description is complete. It explains what the tool does, what the output is (a prompt stack), how to use it (pair with generate_image), and enumerates available choices. No critical information is missing.

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 fully documents both parameters with per-enum descriptions, so baseline is 3. The description adds value by listing the style choices in natural language and framing them with the 'casual captured' vibe, which reinforces the enum semantics and helps the agent understand the aesthetic intent.

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 this tool applies a user-generated content aesthetic, lists the specific style options (phone shot, film point-and-shoot, mirror selfie, car selfie), and explains it returns a prompt stack for generate_image. This distinguishes it from other apply_* siblings by emphasizing casual, real-person realism rather than cinematic or editorial styles.

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?

It provides clear context: use this when you want content that 'looks like a real person captured it casually,' and it guides the workflow by saying 'pair it with generate_image.' It does not explicitly list when not to use it or mention alternative tools, but the style choices and intended pairing make the use case evident.

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