List every direct flight from an airport (airport code), with full schedule detail per destination: airlines, schedule (day + times), flying_min, seasonality, booking URL. Prefer this over N× route_detail when planning from one hub. Data: scheduled passenger routes operating now, with seasonality labels — not fares, not booking, not date-specific schedules.
| Name | Required | Description | Default |
|---|---|---|---|
| airport | Yes | ||
| include_charter | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that data is scheduled passenger routes operating now, includes seasonality labels, and explicitly lists what the tool does not provide. It does not mention response format details or include_charter behavior, but the data-scope caveats are valuable and transparent.
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?
Three sentences, each earning its place: the first states purpose and output, the second gives routing guidance, and the third sets data boundaries. The main action is front-loaded and there is no redundant or filler text.
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 there is no output schema and no annotations, the description does well by naming the output fields, clarifying the input format, and stating data limitations. It still leaves include_charter semantics and the specific airport-code standard (IATA vs. ICAO) unstated, so it is not fully complete.
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 describes the airport parameter only as a string titled 'Airport', and the description usefully clarifies it expects an airport code. However, schema description coverage is 0%, and the optional include_charter parameter is not explained beyond its name and default, leaving its exact effect to inference.
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 opens with a specific verb and resource: "List every direct flight from an airport (airport code)", and enumerates the returned detail fields. It clearly distinguishes itself from the sibling route_detail by positioning itself as the preferred tool for one-hub planning.
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 to prefer this tool over N× route_detail when planning from one hub, which is a clear when-to-use rule. It also states exclusions: not fares, not booking, not date-specific schedules, helping an agent avoid selecting it for those needs.
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 clearly distinct purpose: resolving place names, listing one route's details, listing all destinations from a hub, and finding multi-leg connections. The descriptions explicitly position airport_destinations as the broader alternative to route_detail, removing ambiguity.
All names are lowercase snake_case and readable, but they mix noun phrases (airport_destinations, route_detail) with imperative verbs (find_connections, resolve_airport). A more consistent verb_noun pattern like list_airport_destinations or get_route_detail would improve predictability.
Four tools is well-scoped for a flight-route data server: resolving input, inspecting a single route, expanding a hub, and planning connections. Each tool serves a distinct query type without unnecessary bloat.
The core workflows of route lookup, hub exploration, and connection finding are covered. Minor gaps exist, such as no direct listing of inbound routes to an airport or airline-specific search, but these are workarounds via existing tools.