skills_find_relevant

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

No annotations exist, so description carries full burden. It describes semantic vector search, ranked results with similarity scores, and interaction with the registry. No negative behaviors are disclosed, but the core mechanism is transparent.

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 well-structured with a clear workflow and query tips. While longer than minimal, each section adds value. It could be slightly more concise but is not wasteful.

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 that an output schema exists (though not shown), the description adequately covers how to interpret results via score thresholds and workflow. It does not need to detail return values. The context is complete for using the tool 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 coverage is 0%, so description must compensate. The query parameter is well explained with tips on being task-specific. However, the top_k parameter is not described beyond its default in schema. Given only 2 parameters, partial compensation.

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 purpose: 'Discover relevant skills' via semantic vector search, and positions it as the first step. It distinguishes from siblings like skills_get_body by providing a workflow that calls sibling tools based on score thresholds.

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?

Explicit guidance is provided: call this first at start of any task, workflow with score thresholds (strong match, possible match, no match), and query tips to be task-specific. This clearly tells when and how to use it vs alternatives like skills_get_body.

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