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

No annotations are provided, so the description carries the transparency burden. It discloses the internal process (search 60,000+ skills, AI-score, select top 5, generate use case), which gives the agent a strong expectation of how the tool behaves. It could be improved by mentioning whether it performs any side effects or how long it takes, but the process disclosure is substantial.

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 concise and well-structured: a one-sentence summary followed by a numbered process list and a usage note. Every sentence adds value, and the front-loaded verb 'generate' immediately clarifies purpose. No fluff or repetition.

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 tool's simplicity (1 required parameter, no output schema, no annotations), the description is sufficiently complete. It explains the process, usage context, and hints at the output ('structured use case with skill recommendations'). A minor gap is the lack of detail on the output structure, but this is not critical for invocation.

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% with the 'query' parameter fully described. The description does not add significant parameter semantics beyond the schema, only reinforcing 'given topic or goal' and providing examples in the schema. As per the baseline for high coverage, score 3 is appropriate.

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: 'Generate a use case for a given topic or goal.' It also outlines a concrete multi-step process (search, score, select, generate), distinguishing it from sibling tools like search_skills or score_skills. The verb 'generate' and resource 'use case' are specific and unambiguous.

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 provides explicit guidance: 'Use when a user describes a task and wants a curated AI skill stack.' This clearly indicates the appropriate context. However, it does not explicitly mention alternatives or when not to use this tool, though siblings like search_skills are implied as alternatives for narrower tasks.

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