get_skill

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

No annotations provided, so description carries full burden. It correctly characterizes the operation as a fetch (read-only) and lists the data categories returned. However, it does not disclose potential side effects, auth requirements, or error handling, though for a read operation this is acceptable.

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?

Two concise sentences: first defines what the tool does, second provides actionable usage advice. No filler words or redundancy.

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 single parameter and presence of an output schema (context signal), the description adequately covers purpose, usage context, and data categories. It is complete for an agent to decide when and how to use the tool.

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 already describes the skill_id parameter and provides examples. The description adds value by directing users to list_skills() to obtain valid IDs, which goes beyond the schema.

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?

Description clearly states verb 'Fetch' and resource 'full structured record for one Loreto catalog skill', listing specific categories (artifacts, mcp, safety, etc.). This distinguishes it from siblings like list_skills (which lists all skills) and generate_skills (which creates skills).

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 'Use this before recommending a skill' and explains what to verify (test language, mermaid diagram count, etc.). Lacks explicit when-not-to-use or mention of alternatives, but the context is clear enough given sibling tools.

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