optimize_prompt

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

Describes the AI augmentation process transparently (adds lighting, composition, etc.). No annotations provided, so the description carries full weight; it discloses the main behavioral trait of enhancing prompts without mentioning side effects or permissions.

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?

Three sentences front-loaded with the core purpose, then supporting details. No superfluous words; every sentence earns its place. Under 50 characters.

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 tool's simplicity, two parameters with full schema coverage, and an output schema (existed in context), the description is adequately complete. It lacks details about prerequisites or limitations but covers the essential function.

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 100% and both parameters have descriptions in the schema. The tool description repeats that style is optional and mentions possible values, but adds no new semantics beyond the schema. Baseline score 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 clearly states it enhances prompts for better image generation, with specific details like lighting and composition. It distinguishes from siblings like generate_image by focusing on prompt optimization, but does not explicitly contrast with alternatives like apply_template.

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?

No guidance on when to use this tool versus siblings such as generate_image or edit_image. The claim 'the #1 way to improve generation quality' implies a use case but lacks context for when not to use it or alternatives.

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