triage_skill_request

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

No annotations are provided, but the description fully discloses that the tool returns all existing skills with descriptions to inform decision-making. It clarifies that the LLM makes the routing decision, and there is no indication of destructive side effects.

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 with bullet points, bold text for key actions, and front-loaded with the primary purpose. Every sentence adds value, and the overall length is appropriate for the complexity of the routing logic.

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 triage role, the description fully explains what it returns (list of existing skills with descriptions) and how to use the result. The presence of an output schema is noted, and the description provides sufficient context for correct invocation.

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?

With 0% schema description coverage, the description compensates by providing a detailed explanation of the 'intent' parameter, including what to include (domain, task type, context) and why specificity matters. This adds significant meaning beyond the bare 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?

The description clearly states the tool's purpose: analyzing intent against existing skills to decide the best action (reuse, improve, create). It distinguishes itself from sibling tools like get_skill and request_skill_optimization by specifying when each should be used.

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 instructs to call this BEFORE creating or optimizing a skill. Provides clear routing logic with match thresholds (>=80%, 50-79%, <50%) and names the specific sibling tools to invoke for each case.

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