skill_get

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

No annotations are provided, so the description must cover behavioral traits. It implies a read operation ('Get') and suggests the output is for LLM usage, but it does not specify error behavior (e.g., for missing skills) or side effects. It is adequate but lacks depth.

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 two sentences, concise and front-loaded. The first sentence states the purpose, the second gives a usage hint. Could be slightly more structured, but effective.

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 simple tool with one parameter and an output schema (though details not provided), the description mentions use for LLMs but does not explain what a 'skill' conceptually entails or the output format. It is adequate but misses context for understanding the data model.

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% and the parameter 'name' is well-described in the schema with examples. The description adds no additional meaning beyond the schema, so baseline score of 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 'Get the specified skill for usage with LLMs.' It specifies the verb (get), the resource (skill), and mentions the purpose (for LLMs). This distinguishes it from sibling tools like skill_list, skill_file_get.

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 advises to 'Use list_skills tool to see available skills,' providing a clear prerequisite. However, it does not explicitly state when not to use the tool or suggest alternatives.

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