air-routes.com

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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure, and it excels: it explains the tier selection ('fewest-stops tier... never a mix'), sorting ('sort by flying time'), layover cap ('c ap at 7'), and charter handling ('excluded unless include_charter=true, and never appear inside multi-leg itineraries'). This is rich, non-obvious behavior that an agent needs to know.

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?

The description is dense but purposeful: four sentences, front-loaded with the core function, then behavioral rules, then data scope. Every sentence adds distinct value with no filler or redundant restatements.

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?

The description conveys strong behavioral context but lacks an output schema and never states the shape of returned options (e.g., what fields each connection contains). It also omits the max_flying_min parameter. For a tool with zero annotations and no output schema, this leaves meaningful gaps in the agent's ability to fully use results.

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 0%, so the description must explain parameters. It covers from_airport/to_airport as airport codes, max_stops in the tier logic, and include_charter explicitly. However, it never mentions max_flying_min, leaving that parameter's meaning entirely to the agent's 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: 'Find flight connections between two airports (airport codes).' It clearly distinguishes this tool from siblings like airport_destinations (which lists destinations), resolve_airport (which resolves codes), and route_detail (which gives route details) by focusing on pair-wise connection search with explicit tier logic.

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 provides clear context about when to use the tool: it returns scheduled passenger routes, explicitly stating 'not fares, not booking, not date-specific schedules,' which helps an agent avoid using it for pricing or booking. However, it does not explicitly name alternatives or state when to prefer this over airport_destinations or route_detail.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool handles free-text input, returns multiple possible codes, and uses 3-letter IATA codes. However, it does not mention behavior for ambiguous queries, unrecognized input, or the exact return structure, leaving gaps for an agent relying solely on this text.

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?

The description is two concise sentences with a front-loaded purpose, an illustrative example, and a clear usage instruction. Every sentence contributes value without redundancy.

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 one-parameter resolver with no annotations and no output schema, the description covers the core purpose, input semantics, output format (IATA codes), and when to use it. It could be more explicit about the exact response shape or error behavior, but the essential call-making information is present.

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 only parameter, 'query', has no schema description (0% coverage), so the description must compensate. It does so meaningfully by specifying that the query is a free-text city or airport name and by giving a concrete example. This is sufficient for a single simple parameter.

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 states a specific action ('Resolve a free-text city or airport name to airport codes') with a concrete example ('london' → LHR, LGW, STN, LTN, LCY). It clearly distinguishes this from sibling tools by positioning it as a prerequisite step before other tools.

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 use this tool 'before other tools when the user gives city names,' which gives clear context for when it applies. It does not name specific alternative tools or list exclusion cases, but the instruction is sufficiently directive for typical airport-query workflows.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context about data currency and scope, but it does not state whether the operation is read-only, whether permissions are needed, or how invalid route ids are handled. The provided context is helpful but not comprehensive.

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?

The description is two tight sentences with no filler. The core action, example, data scope, and exclusions are all front-loaded and each sentence 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 tool with no annotations, no output schema, and two parameters (one undocumented in any way), the description leaves important gaps: parameter semantics are mostly unexplained, return shape is not described, and no guidance is given for choosing between this and sibling tools. The data-scope caveats help, but the agent is still under-informed.

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 0%, and the description does not compensate. It only gives an example route id ('OTP-BCN'), hinting at format, but it never explains the required route_id semantics or the meaning of include_charter, which is a non-obvious boolean flag that an agent would likely have to guess about.

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 states a specific verb and resource: 'Detail for one route' and lists what is included (airlines, schedule, seasonality) with a concrete example. It is conceptually distinct from the sibling tools (airport_destinations, find_connections, resolve_airport), but it does not explicitly name or differentiate them, so it stops short of a 5.

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 gives clear context about the data scope ('scheduled passenger routes operating now, with seasonality labels') and explicit exclusions ('not fares, not booking, not date-specific schedules'). This tells an agent what the tool is not for, though it does not name alternative tools for those cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.