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 clearly states that the tool is asynchronous, returns an `id` and `credits_charged` immediately, and explains the completion statuses (`complete`, `error`, `canceled`) and the availability of `downloads` with direct URLs. It also mentions the exact_download_urls behavior of the helper. This is rich, honest, and goes well beyond minimal expectations.

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 well-structured and front-loaded. The first sentence states the core purpose and cost, and the MCP guidance block is organized into concise, directly actionable steps. Every sentence adds value, and it avoids redundant restatement of the schema.

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 everything needed to use this tool correctly in an agentic flow: async behavior, immediate return values, how to retrieve the finished result, which statuses to watch for, and where the output downloads live. Since an output schema exists, detailed return-value documentation is unnecessary. There are no meaningful gaps for calling this tool successfully.

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 coverage is 67%, and the schema already provides useful descriptions for `name`, `content`, and `art_style`, including an example and template list for `art_style`. The description adds little parameter-level meaning beyond the schema, but it also does not need to because the schema is reasonably self-explanatory. A baseline of 3 is appropriate.

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 and resource: 'Create an AI QR code.' This clearly differentiates it from the many sibling image-generation tools in the list, which all have distinct purposes. The tool name and description align, and there is no ambiguity about what the tool produces.

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 explicit guidance on the async workflow: it says the generation starts immediately, returns `id` and `credits_charged`, and instructs the agent to call `wait_for_image_project` or poll the endpoint. It does not explicitly compare this tool to alternative image generators, but the QR-specific scope makes the primary use case obvious, and the async handling instructions are very actionable.

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