airports

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the calculation method ('great-circle distance') and return format ('distance in both kilometers and miles'), which adds useful context. However, it doesn't disclose error handling, precision, or computational characteristics that would help an agent understand behavioral traits.

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 perfectly concise with two sentences that each earn their place. The first sentence explains what the tool does and its inputs, while the second explains the output format. There's zero wasted language and the information is front-loaded appropriately.

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 relatively simple tool with 2 parameters, 100% schema coverage, and no output schema, the description provides adequate context. It explains the calculation method, input format, and output units. However, without annotations or output schema, it could benefit from more behavioral context about error cases or limitations.

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%, with both parameters ('from' and 'to') clearly documented in the schema. The description adds no additional parameter information beyond what the schema provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in description.

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 the specific action ('calculate the great-circle distance'), the resource ('between two airports'), and the identification method ('by their IATA codes'). It distinguishes itself from sibling tools like 'get_airport' and 'search_airports' by focusing on distance calculation rather than airport information retrieval.

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 implies usage when distance between airports is needed, but provides no explicit guidance on when to use this tool versus alternatives. There's no mention of prerequisites, limitations, or comparison with other distance calculation methods. The context is clear but lacks specific when/when-not instructions.

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 provided, the description carries the full burden of behavioral disclosure. It describes what information is returned (name, city, country, coordinates, altitude, timezone) and the input requirement (IATA code), but doesn't mention error handling, rate limits, authentication needs, or whether the data is static or real-time. It adequately describes the core behavior but lacks operational context.

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 perfectly concise and front-loaded. The first sentence states the complete purpose and input requirement, and the second sentence lists the return values. Every sentence earns its place with no wasted words or 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?

Given the tool's low complexity (single parameter, no annotations, no output schema), the description is reasonably complete. It explains what the tool does, what it requires, and what it returns. The main gap is the lack of output schema, but the description compensates by listing the return fields. For a simple lookup tool, this is nearly 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?

Schema description coverage is 100%, so the schema already fully documents the single parameter. The description adds value by providing examples ('JFK', 'LHR', 'NRT') and clarifying it's a three-letter code, but doesn't add significant semantic meaning beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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 the tool's purpose with specific verb ('Get detailed information') and resource ('airport'), and distinguishes it from siblings by focusing on individual airport lookup rather than distance calculation or search. It explicitly mentions the IATA code requirement, which differentiates it from search_airports.

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 for when to use this tool (getting detailed info about a specific airport by IATA code), but doesn't explicitly state when not to use it or name alternatives. The sibling tool names suggest alternatives (calculate_distance, search_airports), but the description doesn't guide the agent on choosing between them.

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 key behavioral traits: it's a search operation (implying read-only, non-destructive) and specifies a pagination limit ('Returns up to 30 results per page'). However, it lacks details on permissions, rate limits, error handling, or the exact return format, which are important for a tool with no 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?

The description is appropriately sized and front-loaded: two concise sentences that directly state the purpose and key behavioral constraint (pagination limit). Every sentence earns its place with no wasted words, making it efficient and easy to parse.

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 the tool's moderate complexity (search with pagination), no annotations, and no output schema, the description is partially complete. It covers the basic operation and pagination but lacks details on output structure, error cases, or integration with sibling tools. It's adequate as a minimum viable description but has clear gaps for full contextual understanding.

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%, so the schema already documents both parameters ('query' and 'page') thoroughly. The description adds minimal value beyond the schema: it reiterates that 'query' can be for 'name, city, or country' (which is in the schema) and implies pagination with 'per page' (aligned with the 'page' parameter). Baseline 3 is appropriate as the schema does the heavy lifting.

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 the tool's purpose: 'Search for airports by name, city, or country.' It specifies the verb (search) and resource (airports), and mentions the searchable fields. However, it doesn't explicitly differentiate from sibling tools like 'get_airport' (which likely retrieves a single airport by ID) or 'calculate_distance', so it doesn't reach the highest score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_airport' or 'calculate_distance', nor does it specify scenarios where this search tool is preferred over direct retrieval or other operations. Usage is implied by the purpose but not explicitly stated.

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