suggest_trending_design

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'suggests and applies,' which is ambiguous about whether it modifies an existing screen, generates a new one, or has destructive side effects. It also does not mention any permissions, reversibility, or what happens to the projectId.

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, efficient sentence that front-loads the verb and resource, then adds concrete examples without any fluff. Every word earns its place, and it is neither over- nor under-specified for the information it conveys.

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 is too sparse for a tool with no output schema and no annotations. It does not explain what 'applies' means, what the function returns, or how the tool interacts with the provided prompt and projectId. Given the large sibling set, this leaves a noticeable ambiguity that could lead to incorrect usage.

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 description coverage is 100%, so the baseline for this dimension is 3. The description adds a small amount of value by naming example trends, but the schema already documents all parameters with descriptions, enums, and defaults. There is no additional parameter meaning provided in the description.

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 the tool's function with a specific verb and resource: 'suggests and applies modern UI/UX design trends to a screen prompt.' It also lists concrete example trends (glassmorphism, bento-grid), which helps the agent form a mental model. However, it does not explicitly distinguish itself from closely related siblings like apply_design_context or generate_dark_mode.

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 the tool should be used when a screen prompt needs modern design trends applied, but it offers no explicit guidance on when to choose this over alternatives or when not to use it. There are many design-related sibling tools, and without exclusions or contexts, the agent may find it hard to disambiguate.

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