list_servicesWhat Iconic CLS runs, what each service needs in order to be priced, which airports and private airfields are covered, and where a human books. Read this before quoting.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false, so the description isn't burdened with safety disclosure. It adds valuable context about the tool's contents (pricing needs, coverage areas) and notes that a human books, implying manual steps. It does not contradict 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?
Two sentences with no filler. The first sentence packs the core purpose and scope, while the second provides a clear action directive. Every word earns its place.
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 zero-parameter reference tool without an output schema, the description covers all essential aspects: what it lists, when to use it (before quoting), and how it relates to the sibling tool. The absence of output format details is acceptable given the simple informational nature.
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 zero parameters and 100% schema coverage, there is nothing to explain about parameters. The description appropriately focuses on the informational value rather than parameter details, matching the baseline for parameterless tools.
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 lists what Iconic CLS runs, including pricing prerequisites, covered airports/private airfields, and where human booking occurs. This distinguishes it from the sibling tool 'quote_trip' by specifying its informational scope.
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 explicit instruction 'Read this before quoting' directly tells the agent when to use this tool relative to the 'quote_trip' sibling. It also enumerates the content areas covered, making it clear it serves as a prerequisite reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose: listing services, quoting a trip, and booking a trip. There is zero overlap in function, making selection unambiguous.
All tool names follow a consistent verb_noun pattern (list_services, quote_trip, book_trip) with snake_case throughout. The naming is predictable and uniform.
With only 3 tools, the set is minimal but aligned with the server's narrow scope of a car service booking flow. It feels slightly thin but not unreasonable; each tool earns its place.
The surface covers the core workflow (list, quote, book), but lacks tools for checking trip status, modifying, or cancelling a booking—those are handled externally via phone, creating a notable gap for agents.