generate_ai_image_prompt_blueprint

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It states that it generates prompts but does not describe the output format (single prompt vs. variations), any side effects, determinism, or limitations. For a content-generation tool with no output schema, this is a significant gap that leaves the agent uncertain about the return value.

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, front-loaded sentence with no wasted words. It conveys the action, target models, and examples efficiently. However, the examples (e.g., 'hero visual backgrounds') do not exactly match the enum values (e.g., 'hero_background_glow'), which could cause slight confusion. Still, it is concise and to the point.

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 tool is relatively simple (2 flat params, 1 enum), but with no output schema, the description should at least hint at what the generated prompt looks like or how many are returned. It doesn't. For an agent deciding whether to use this tool, the missing output format is a moderate gap, making it adequate but not fully complete.

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 provides 100% coverage with descriptions for both parameters, including an enum for asset_type. The tool description adds minimal value beyond the schema—it merely reiterates example asset types in prose without deepening understanding of parameter formatting or constraints. Baseline 3 is appropriate given 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 clearly states a specific verb ('generates'), a specific resource ('tailored prompts'), and the target models (Midjourney / DALL-E / Flux). It lists concrete asset types (hero visual backgrounds, 3D app mockups, glassmorphic icons) and audience (web/mobile apps), which distinguishes it from sibling blueprint generators that produce text/copy. The purpose is unmistakable.

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 implies when to use this tool (when you need image prompts for visual assets) but does not explicitly state when it is better than alternatives or when not to use it. There is no mention of exclusions or alternative tools, leaving an agent to infer usage from the tool name and description. This is adequate but not explicit.

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