optimize_prompt

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

No annotations are provided, so the description carries the burden. It states the transformation behavior (simple to detailed) and mentions 'using Ketchup AI', but it does not disclose return format, side effects, permissions, or rate limits. For a simple transformation this is minimal but not rich behavioral context.

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 a single sentence of 13 words, front-loaded with the verb 'Optimize', and contains no redundant or filler text. Every word adds value.

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 one-parameter tool with no output schema, the description adequately explains the purpose and implies the return value (the optimized prompt). It could mention the output format explicitly, but the statement 'into a detailed professional prompt' covers the essential outcome, making it complete enough for the tool's simplicity.

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 schema description coverage is 100% for the only parameter 'prompt', with an example. The description adds the term 'drawing' but does not materially go beyond the schema's meaning. Baseline of 3 is appropriate due to high schema coverage.

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 uses a specific verb 'Optimize' and a resource 'simple drawing prompt' with a clear goal of producing a 'detailed professional prompt'. This distinguishes it from the sibling tool generate_image, which creates images rather than enhancing prompts.

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 clearly implies when to use the tool: when you have a simple prompt and need a more detailed one. It does not explicitly name alternatives or exclusions, but the context of the sibling generate_image suggests a workflow of optimizing first then generating. This meets the 'clear context, no exclusions' level.

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