get_tail_infoWiFi provider history for one aircraft by tail number, including crowd-sourced reports and fleet assignment. Use when the exact airframe is known.
| Name | Required | Description | Default |
|---|---|---|---|
| tail_number | Yes | Aircraft registration / tail number, e.g. "N12345" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds useful context about the data sources (crowd-sourced reports, fleet assignment) and that it's a historical view, which goes beyond what annotations provide. No contradictions with 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, front-loaded with the core function and followed by a clear usage directive. Every word earns its place, with no redundant information.
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, good annotations, and no output schema, the description effectively communicates the tool's purpose and data coverage. It doesn't need to explain return formats or pagination given the simple query nature, making it complete for the context.
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 coverage is 100% for the single tail_number parameter, which includes an example format. The description reinforces that it's for 'one aircraft' but adds no new syntax or semantic details beyond what the schema already provides, so baseline 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 it provides 'WiFi provider history for one aircraft by tail number' with specific content ('crowd-sourced reports and fleet assignment'). This is a specific verb-resource-scope combination that distinguishes it from sibling tools like get_airline_wifi (airline-level) and get_flight_wifi (flight-level).
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 description explicitly says 'Use when the exact airframe is known,' giving a clear when-to-use condition. It doesn't explicitly mention alternatives or when-not-to-use, but the condition implies other tools are for less specific queries.
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.