get_airline_wifiWiFi providers an airline uses fleet-wide, plus a fleet summary and whether WiFi is free. Use when the question is about the airline rather than one flight.
| Name | Required | Description | Default |
|---|---|---|---|
| airline_code | Yes | IATA airline code, e.g. "UA" for United, "DL" for Delta |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint and openWorldHint annotations already cover the safety and openness profile. The description adds useful behavioral context by explaining the scope ('fleet-wide') and the composition of the result ('providers, fleet summary, free status'), which goes beyond what annotations alone provide.
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 short sentences: the first conveys the core functionality, and the second gives usage guidance. No wasted words, and the key information is front-loaded.
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 simple tool with one parameter and an effective schema description, the tool description fully covers what the agent needs to know to invoke it correctly. It explains what results to expect and when to use the tool, making it complete for its complexity level.
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% for the single parameter airline_code, including an example format. The description adds no additional parameter semantics, so the baseline of 3 is appropriate.
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 what the tool returns: 'WiFi providers an airline uses fleet-wide, plus a fleet summary and whether WiFi is free.' It also distinguishes itself from flight-level tools by noting 'Use when the question is about the airline rather than one flight,' which separates it from get_flight_wifi.
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?
Explicit guidance is provided: 'Use when the question is about the airline rather than one flight.' This tells the agent when to use this tool, but it does not name the specific alternative tool for flight-level queries, so it stops short of the most explicit form of guidance.
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.
Most tools have distinct purposes, but get_flight_wifi and get_wifi_facts both answer flight-level WiFi questions, creating overlap. The descriptions help by directing users to get_wifi_facts as the preferred choice, yet the redundancy remains. Other tools like get_airline_wifi vs list_airlines are differentiated by scope, but the core flight lookup is duplicated.
All tool names follow a consistent verb_noun pattern in snake_case: get_airline_wifi, get_flight_wifi, get_rollouts, get_speed_stats, get_tail_info, get_wifi_facts, list_airlines, search_wifi. The verbs (get, list, search) are appropriate and uniform. No mixed naming conventions or camelCase deviations are present.
The 8 tools are well-scoped for a WiFi information server, covering airline, flight, aircraft, speed, rollout, and search capabilities without overwhelming redundancy. Each tool serves a distinct need (except the noted overlap), and the count sits comfortably in the ideal range.
The tool set comprehensively covers the in-flight WiFi domain: airline-wide info, flight-specific predictions, tail history, speed statistics, rollout progress, and free-text search. No critical operations are missing, and the inclusion of both airline and flight level lookups with fallback logic makes the surface complete for read-only information retrieval.