ai_enhance_pattern

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 AI suggestions but doesn't disclose behavioral traits like whether this is a read-only or mutating operation, what happens to the original pattern, authentication requirements, rate limits, or expected response format. The description is too vague about the actual behavior beyond the basic action.

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 gets straight to the point without unnecessary words. It's appropriately sized for a tool with three parameters and clear schema documentation. However, it could be slightly more front-loaded with key differentiators.

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 annotations, no output schema, and parameters that control AI-based pattern modification, the description is insufficient. It doesn't explain what 'current pattern' refers to, what happens after enhancement, error conditions, or performance characteristics. The context signals show this is a mutation tool (implied by 'modify'), but the description lacks critical behavioral details.

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 parameters are fully documented in the schema. The description adds no additional parameter semantics beyond implying that parameters control the enhancement process. It doesn't explain relationships between parameters (e.g., how 'target_style' interacts with 'enhancement_type') or provide usage examples.

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 action ('enhance or modify') and resource ('current pattern') with the mechanism ('using AI suggestions'). It distinguishes from siblings like 'ai_generate_pattern' (creates new) and 'ai_suggest_variations' (specific enhancement type). However, it doesn't specify what constitutes a 'pattern' in this context, leaving some ambiguity.

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. While it implies usage when AI-based pattern enhancement is needed, it doesn't mention when to choose specific enhancement types or how it differs from siblings like 'generate_variation' or 'ai_suggest_variations'. The description provides no exclusions or prerequisites.

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