suggest_improvements

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

No annotations are provided, so the description must fully disclose behavior. It only states 'AI-powered', which hints at computational cost but does not specify if the tool is read-only, modifies the design, or requires permissions. No side effects, rate limits, or output format are mentioned.

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?

A single, short sentence that is efficient and direct. However, it could benefit from additional structure (e.g., separating purpose from source). No wasted words, but slightly underdeveloped.

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 tool with no output schema and no annotations, the description should provide more context about what kind of improvements are suggested, how they are presented, and any limitations. The current description is too brief to fully inform an agent's decision.

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% (nodeId described as 'Node to analyze'). The description adds no further parameter information beyond the schema. Per instructions, baseline 3 is appropriate when schema already documents parameters adequately.

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 it provides 'AI-powered design improvement suggestions', which is a clear verb+resource combination. It distinguishes itself from siblings like 'suggest_color_palette' and 'suggest_type_scale' by being more general, though it doesn't explicitly differentiate. The phrase 'design intelligence engine' adds context but could be more specific.

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 alternatives like 'suggest_color_palette' or 'design_from_prompt'. There is no mention of prerequisites (e.g., must have a design selected) or exclusions. The agent is left to infer appropriate usage from context.

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