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

With no annotations, the description carries full disclosure burden. It explains the tool fills in user inputs, returns an ordered recipe to execute, and tells the agent to ask the user for inputs if omitted. It doesn't elaborate on return format or execution semantics, but covers the core behavior well.

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?

Four sentences, each serving a distinct purpose: definition, return value, usage preference, and parameter routing. The front-loaded sentence captures the essence, and the structured guidance is dense without being verbose.

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 no output schema, the description compensates by explicitly stating the return value ('ordered recipe of tool calls') and the workflow with list_skills. It prepares the agent to execute the playbook and handle unnamed skills, covering all functional gaps.

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 description coverage is 100%, so baseline is 3. The description adds value by giving a concrete example of inputs and skill_id, and clarifies that inputs are optional and what happens if omitted — going beyond the schema's static descriptions.

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 opens with a specific verb+resource: 'Get a ready-made skill's step-by-step playbook' and clarifies it returns an 'ordered recipe of tool calls'. This clearly distinguishes it from sibling data-fetching/search tools and positions it as a meta-tool that produces executable instructions.

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 'PREFER running a matching skill over improvising raw searches' and provides a decision tree: if the user names a skill, pass the skill_id directly; otherwise call list_skills first. This is textbook usage guidance with clear alternatives.

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