ai_suggest_layout

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

No annotations are provided, so the description carries full burden. It mentions 'suggests layouts' but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires specific permissions, what the output looks like (e.g., visual suggestions, data structures), or any rate limits. The description is minimal and lacks essential context for safe and effective use, especially for an AI-driven tool that might involve complex processing.

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, concise sentence in Korean ('캔버스 크기에 맞는 레이아웃을 제안합니다'), which translates to 'Suggests layouts fitting canvas size.' It's front-loaded with the core purpose and wastes no words. However, it could be more structured by including key details, but as-is, it's efficient 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?

Given the complexity of an AI suggestion tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'suggests' means in practice, what the output entails (e.g., visual layouts, coordinates, recommendations), or any behavioral aspects. For a tool that likely involves AI processing and returns layout data, this minimal description leaves significant gaps for an agent to understand and use it correctly.

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 schema already documents both parameters (contentType with enum values and elementCount with range). The description adds no additional meaning beyond what the schema provides—it doesn't explain how these parameters influence layout suggestions or their interaction. Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate with extra insights.

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 states the tool 'suggests layouts fitting canvas size' which provides a general purpose, but it's vague about what 'suggests' entails (e.g., generates, recommends, returns). It distinguishes from siblings like drawing or export tools, but doesn't clarify how it differs from other AI tools like ai_suggest_colors. The verb 'suggests' is somewhat ambiguous, and the resource 'layout' is clear but lacks specificity about output format.

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 explicit guidance on when to use this tool versus alternatives is provided. The description implies usage for layout suggestions based on canvas size, but it doesn't mention when not to use it, prerequisites, or how it compares to other layout-related tools (none are listed in siblings). Without context on alternatives, the agent must infer usage from the tool name and parameters alone.

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