get_skill

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

No annotations are provided, so the description carries the burden. It implies a read-only operation by stating it 'fetches' data and returns metadata, without mentioning side effects. It could explicitly confirm non-destructiveness, but the behavior is clear enough.

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 and front-loaded. It is concise but includes essential usage guidance and outcomes. Every sentence contributes meaning, though a slight reduction in length is possible without losing clarity.

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 (one parameter, no output schema), the description is comprehensive. It lists the returned fields and provides troubleshooting advice. It adequately covers the tool's context and user expectations.

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?

The input schema already covers the slug parameter with an example, giving a baseline of 3. The description adds value by specifying the slug must be an 'exact lowercase hyphen-separated slug from a previous result', reinforcing correct usage and validation constraints.

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 uses a specific verb 'Fetch detailed metadata for one AI skill by exact slug', clearly identifying the resource and scope. It distinguishes itself from sibling tools like search_skills and popular_skills by focusing on a single skill retrieval via slug.

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 explicitly states when to use this tool ('after search_skills or popular_skills returns a slug, or when the user provides a known slug'), what not to do ('Do not guess slugs'), and provides fallback guidance ('If the slug is not found, search again with related keywords').

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