run_skill

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

Annotations are all false and provide little safety information. The description adds key behavioral context: the tool only returns the skill body for the LLM to execute, rather than executing it directly. It also clarifies that the task is optional, which goes beyond the raw schema and annotations.

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 three concise sentences. The first states the action, the second explains the result and how the LLM uses it, and the third points to the sibling discovery tool. Every sentence earns its place with no redundancy or filler.

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?

For a low-complexity tool with two parameters and no output schema, the description sufficiently explains what it returns (the skill body) and how to find skill names. It does not detail the structure of the playbook, but that is not essential for invoking the tool correctly. Overall, the description is complete enough for correct selection and use.

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%, with both 'name' and 'task' already described well in the input schema. The description adds slight semantic clarity by calling the task 'optionally' and saying it is applied to the skill, but it mostly mirrors the schema, so it does not meaningfully elevate understanding beyond what is already structured.

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 states a specific verb and resource: 'Fetch the playbook for a named skill' and clarifies the output: 'Returns the skill body for the LLM to execute step-by-step.' It clearly distinguishes from the sibling list_skills by pointing to it as a discovery tool, making the tool's own purpose unambiguous.

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 gives usage context: it is for executing a named skill with an optional task, and it explicitly names list_skills to view available skills. This is helpful but does not state explicit when-not-to-use cases or mention any alternative execution tools, so it falls just short of a 5.

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