route_and_execute

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

With no annotations, the description carries the burden of disclosure. It explicitly states that the tool not only selects but also executes the skill automatically, and it mentions a fallback message for unmatched inputs. This goes beyond the name and gives useful behavioral context.

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 concise, front-loaded with the main purpose, and structured with Args/Returns blocks that add value without redundancy. Every line contributes to understanding the tool's function and output.

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 single-parameter router tool with no annotations, the description is sufficiently complete. It explains the input, the execution behavior, and the return type. It does not enumerate possible skills, but that is not necessary given the tool's dispatch role and the presence of an output schema.

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 schema only provides a title for user_input with no description, so the description's Args block ('Natural language instruction') adds meaningful semantics. This compensates for the 0% schema coverage by explaining what the parameter should contain.

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 routes natural language input to the best matching skill and executes it, which is a specific verb+resource combination. It distinguishes itself from sibling tools like query_knowledge or ingest_pdf by acting as an orchestrator that selects among them.

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 usage is implied: when you have a natural language instruction, use this tool to route it to a skill. However, there is no explicit guidance on when to use this directly vs. calling a specific sibling tool, nor any when-not-to-use conditions or alternatives.

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