skills_find_relevant

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

With no annotations, the description bears full responsibility. It describes a non-destructive semantic search returning ranked similarity scores. Lacks details like error handling or registry emptiness, but it is transparent enough for safe use.

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 first sentence, then workflow steps and tips. It is concise yet informative, using bullet points effectively. Minor redundancy could be trimmed, but overall efficient.

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 search nature, the description covers the core workflow and parameter usage. The existence of an output schema reduces the need to detail return values. It is sufficiently complete for an agent to execute 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%, but the description provides rich context for the 'query' parameter with examples and tips. However, 'top_k' is not explained beyond its default, leaving some ambiguity. Adequate but not exhaustive.

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. It is clearly distinct from sibling tools (e.g., skills_get_body retrieves body, skills_list_all lists all), using specific verbs and context.

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?

Explicitly says 'Call this FIRST' and provides a detailed workflow with score thresholds (>0.6, 0.4–0.6, <0.4) and corresponding actions. Also gives query tips for better results, offering clear guidance on when and how to use the tool.

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