All tracked airlines
list_airlinesEvery airline SeatWiFi tracks, with its WiFi providers. Large response — use search_wifi or get_airline_wifi when you know which airline you want.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_airlinesEvery airline SeatWiFi tracks, with its WiFi providers. Large response — use search_wifi or get_airline_wifi when you know which airline you want.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely new context with the 'large response' warning, which tells the agent this call is expensive to pull into context. It does not say whether results are paginated or how many airlines to expect, leaving a minor gap.
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, both front-loaded with the decisive information: what it returns first, then the size caveat and alternatives. Nothing is repeated from the title or schema and no sentence is filler.
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 enumeration tool with no output schema, the description covers the return shape ('with its WiFi providers'), the operational cost, and the alternatives. There is nothing else an agent needs before calling it.
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?
Zero parameters and 100% schema coverage, which is the baseline-4 case. The description appropriately spends no words on parameters and instead uses the space for routing and response-size guidance.
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?
States exactly what is returned: every airline tracked, paired with its WiFi providers. It explicitly distinguishes itself from siblings search_wifi and get_airline_wifi by naming them, so an agent can tell which tool enumerates the full corpus vs. which fetches a specific record.
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?
Gives explicit when-not-to-use guidance: use search_wifi or get_airline_wifi when the target airline is already known. Combined with the 'large response' warning, the agent has both the routing rule and the cost signal needed to choose correctly.
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.