generate_photo

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

Given no annotations, the description attempts to disclose behaviors: credit cost and prerequisite upload. However, it omits details about the generation process (e.g., whether it is synchronous or async, what happens on error, or how the wait_for_result parameter affects behavior). This leaves some ambiguity for the agent.

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 extremely concise at three sentences, with no redundant information. It front-loads the core purpose and follows with essential usage guidance in a logical order. Every sentence earns its place.

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 the tool's purpose, prerequisites, and cost, and mentions the key distinction between themed and custom generation. However, it does not explain the conditional dependency between type/category/prompt, nor describe the output format (e.g., image URL or prediction ID) despite having a wait_for_result parameter. Given the complexity (9 params, no output schema), slightly more detail would improve completeness.

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?

With 100% schema description coverage, the schema already documents all parameters. The description adds value by explaining the credit cost and linking category usage to browse_themes, but does not clarify conditional requirements (e.g., when type=themed vs custom). Baseline 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 explicitly states the tool generates AI photos from face images using themed styles or custom prompts. It clearly identifies the verb 'generate', the resource 'AI photos', and the method, and distinguishes itself from sibling tools like upload_image and browse_themes by referencing them as prerequisites or discoverability tools.

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: it requires prior face image upload via upload_image, costs 100 credits per photo, and recommends browse_themes for theme discovery. It does not explicitly state when not to use this tool (e.g., for other media types), but the sibling tools cover those purposes, and the guidance is sufficient for an informed selection.

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