Aviationstack MCP Server

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the current-day-only limitation, optional airline filtering, and the per-flight fields returned. This is strong for a read-only schedule tool, though it does not discuss ordering or data availability.

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 compact sentences with no filler: the core action and scope are front-loaded, followed by useful return-field details and the key routing to the future-date sibling.

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 covers purpose, scope, key returned fields, and the critical date limitation. The schema fully documents parameters and the output schema covers return structure, so nothing essential is missing for correct invocation.

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 all four parameters are already documented. The description adds context by linking schedule_type to arrival/departure boards and mentioning airline_name filtering, but it does not add new syntax or format detail beyond the schema.

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 a specific verb ('Return') and resource: today's arrival or departure board for an airport, with an optional airline filter. It also names the sibling future_flights_arrival_departure_schedule, making it easy to distinguish from the related tool.

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?

Explicitly scopes the tool to the current day and directs the agent to future_flights_arrival_departure_schedule for any later date. This gives clear when-to-use guidance and an explicit alternative, leaving no inference required.

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 behavioral disclosure itself. It communicates the live nature of the data, the optional status narrowing, and exactly which fields will be returned. It does not discuss auth, rate limits, or empty-result behavior, but these are not critical for a read-only lookup.

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 with no wasted words: purpose first, return fields second, routing to the sibling third. Every sentence contributes distinct value.

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, full parameter docs, and existing output schema together cover the main contract. Minor gaps remain around API limitations (rate limits, live-data freshness guarantees), but an agent knows what to call, with what inputs, and what kind of output to expect.

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 airline_name, flight_status, and number_of_flights. The description only restates the optional status narrowing and adds no new parameter-level meaning, matching the baseline for high schema coverage.

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-resource pair ('Return live flights for one airline') and an optional filter, and then explicitly contrasts it with get_flight_status. An agent can tell exactly what this tool does and how it differs from its nearest sibling.

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?

It gives an explicit when-to-use cue ('survey an airline's current activity') and points to get_flight_status for the known-flight-number case, but it does not mention exclusions for historical or schedule-based siblings such as historical_flights_by_date. Context is clear, but exclusions are partial.

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 burden. It openly states the future-date limitation, the fact that the board is scheduled rather than live, and the outputs returned. It doesn't discuss error conditions or default behavior when date is omitted, but those are minor for a read-style query tool.

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 tight sentences: the main action, the applicable date window, the output fields, and the sibling alternative. Every sentence earns its place and no information is repeated except the deliberate emphasis of the next-7-days coverage.

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 moderately parameterized tool with a rich input schema and an output schema, the description covers purpose, temporal scope, return contents, and the key alternative. Nothing essential to selecting or invoking the tool correctly is missing.

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%, so the schema already documents date format, airport code, airline filter, schedule_type values, and number_of_flights. The description adds no parameter-level meaning beyond emphasizing the future-date window, so the baseline of 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?

States a specific action and resource: returns the scheduled arrival/departure board for an airport on a future date. It further defines the date window and explicitly routes today's board queries to flight_arrival_departure_schedule, so it is clearly distinguished from the sibling.

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?

Explicitly says this tool covers tomorrow through about 12 months ahead and names flight_arrival_departure_schedule as the tool to use for today's board instead. This gives clear when-to-use and when-not-to-use guidance.

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 transparency burden. It does this well by detailing what the response contains—scheduled, estimated, and actual times, terminal, gate, baggage belt, delay minutes, and both ends of the flight—and by disclosing that the operating flight is ordered ahead of codeshares. It does not discuss not-found behavior, but that is a minor gap for a lookup tool.

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 three tightly packed sentences: core purpose, return-value summary, and usage guidance with alternatives. It front-loads the most important information and every sentence earns its place without unnecessary wording.

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 two-parameter lookup tool with an output schema, the description is complete. It explains the search key, date behavior, the scope of returned data, the ordering nuance, and when to choose sibling tools instead. Nothing essential for correct invocation is missing.

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%, so the schema already documents both parameters with descriptions and examples. The description adds some useful context around the date default and the IATA number, but it does not significantly deepen parameter meaning beyond what the schema already provides.

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 uses a specific verb and resource: 'Look up one specific flight by its IATA flight number' and clearly scopes the operation to 'the current day or a given date.' It also differentiates from sibling tools by emphasizing a single flight and by listing distinct return data like actual times, gate, baggage belt, and delay minutes.

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 states when to use this tool ('when the question names a flight number') and names concrete alternatives for related cases: flights_with_airline for browsing an airline's flights and historical_flights_by_date for past dates. This gives an agent clear routing guidance.

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 transparency burden. It discloses the Basic plan requirement, the historical scope, the optional filters, and the data fields returned. It does not discuss edge cases such as invalid dates, empty results, or date-range limits, but the plan requirement and output scope are meaningful behavioral 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?

Three concise sentences deliver the core purpose, filter options, return fields, plan requirement, and sibling routing without redundancy. The most important usage constraint is front-loaded.

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 historical list tool with a full output schema and sibling tools, the description covers what the tool does, when to use it, what it returns, which plan it requires, and which alternatives to use instead. Nothing essential is missing for an agent to select and invoke it correctly.

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 input schema already documents all five parameters with descriptions, and coverage is 100%, so the baseline is 3. The description adds a small amount of context by referring to 'route filters' and listing return fields, but it does not materially go beyond the schema's parameter documentation.

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 uses a specific verb and resource: 'Return flights that already operated on a past date.' It clearly distinguishes this tool from its siblings by emphasizing 'past date only' and naming the alternatives for today and future dates.

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 explicit when-to-use guidance: 'Use this for past dates only.' It also names two sibling tools for the other time contexts, making the selection decision explicit and unambiguous.

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, and the description carries the behavioral burden well: it discloses one-page-at-a-time pagination, the pagination block with limit/offset/total, and the presence of operational status. It does not explicitly address rate limits or plan requirements in the description, but the schema already carries the Basic plan note and the operation is inherently read-only.

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 front-loaded with the core purpose and is free of filler. The field-list sentence is useful but partly duplicates what the output schema already documents, keeping it just below a perfect 5.

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 read-only, paged catalog-listing tool with all parameters described in the schema and an output schema available, the description is sufficient. It covers the operation, the return shape, pagination, and the key integration use case for flight tools.

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%, so the baseline is 3, but the description adds meaning beyond the schema by telling the agent that search is the mechanism to resolve a user-supplied airline name to the IATA code expected by flight tools. It also frames limit/offset in terms of the pagination block returned.

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 a specific verb and resource: 'List airlines from the reference catalog,' with pagination and optional search. The 'airlines' scope distinguishes it from sibling catalog tools like list_airports and list_routes, and the record-field list makes the resource concrete.

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?

It provides a clear practical use: 'Use search to resolve an airline name to the IATA code the flight tools expect,' which positions the tool as the reference lookup for flight-related siblings. It does not explicitly name when-not-to-use alternatives, so it misses the top tier.

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 transparently explains pagination behavior, optional search, and the shape of each record including the pagination block. It does not mention auth or rate limits, but for a read-only catalog listing the disclosed behavior is thorough and accurate.

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 tightly written in three sentences: a clear action statement, a record contents overview, and a practical use-case note. Every sentence contributes meaningful information, and the most important purpose is front-loaded.

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, all-optional-parameter list tool with an output schema present, the description covers everything an agent needs: operation, pagination semantics, record fields, search behavior, and the intended downstream use. No critical information appears missing.

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%, so the baseline is 3, but the description adds meaning beyond the schema by explaining how pagination works ('one page at a time', 'pagination block carrying limit, offset and total') and framing 'search' as the mechanism to resolve names to IATA codes for flight tools. This is useful contextual value that the parameter descriptions alone do not fully convey.

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 identifies the operation ('List'), the resource ('airports from the reference catalog'), and key distinguishing features like pagination and optional text search. It also explains each record's contents and the intended use case for resolving airport names to IATA codes, making it easy to differentiate from sibling list 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 gives clear context for when to use this tool: when you need airport reference data or need to resolve an airport name to the IATA code expected by flight tools. It does not name alternatives or state explicit exclusions, but the resource focus and sibling names are sufficiently distinct that no confusion is likely.

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 behavioral burden and does so well: it discloses pagination behavior, response shape, filter semantics, and plan requirements. It does not mention sorting or rate limits, but those are minor for a read-only listing operation.

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 densely informative sentences with no filler. The purpose and key scoping (filters, pagination) are front-loaded, followed by response details and a clear alternative, all in an efficient structure.

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 is complete for a filtered, paginated list tool: it covers what it returns, how filters and paging work, the key limitation, and the authentication/plan requirement. The rich input schema and output schema handle the remaining details.

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%, so the baseline is 3. The description adds meaningful value beyond the schema by clarifying that filters can be combined in any combination and that results are returned one page at a time with a pagination block.

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 a specific verb ('List'), a clear resource ('scheduled routes'), and the available filters. It also explicitly differentiates itself from get_flight_status by clarifying this describes route existence rather than flight operation.

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?

Provides explicit when-to-use context ('filtered by any combination...') and an explicit alternative for the related case ('use get_flight_status for that'). It also discloses the plan prerequisite, which is important for invocation decisions.

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 reveals the pagination model, record structure (tax id, tax name, IATA code), the static reference data nature, and the paid plan prerequisite. This goes beyond what the schema provides, though it omits details like rate limits or error behavior.

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?

Every sentence earns its place: the first states the core action, the second describes the response shape, and the third clarifies data type and access requirement. It is concise, front-loaded, and free of 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 straightforward list tool with three optional parameters and an output schema, the description is complete. It explains what is returned, pagination semantics, the nature of the data, and the prerequisite paid plan. No critical missing information is apparent for an agent to invoke it correctly.

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 baseline is 3. The description does echo the search and pagination parameters conceptually, but it does not add meaningful semantic detail beyond what the input schema already documents for limit, offset, and search.

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 ('List'), resource ('aviation taxes from the reference catalog'), and key behaviors (pagination, optional text search). It also distinguishes the tool from fare/booking charge data by clarifying it is static reference data, which separates it from potentially confusing uses and sibling 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 provides clear context on when to use the tool: for static reference data, not for fares or amounts charged. It also notes the paid plan requirement. However, it does not explicitly name alternative tools or state when not to use this tool in favor of a sibling, so it falls short of a 5.

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 and does so well. It discloses the random-offset mechanism, that repeated calls return different rows, and that the tool only samples without a search parameter. This goes well beyond a generic 'returns random data'.

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 front-load the main purpose, then record fields, then the behavioral caveat. Every sentence earns its place; no redundancy or 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 simple one-parameter sampler, the description covers all essential behaviors: random selection, record fields, non-determinism across calls, and the impossibility of lookup. The presence of an output schema means return-value detail does not need to be restated.

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%: the schema fully describes number_of_aircraft as an integer 1-100 with exclusiveMinimum 0. The description does not add material parameter information beyond confirming this is a sample count, so the baseline of 3 applies.

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 action and resource: 'Return a random sample of aircraft types from the Aviationstack reference catalog.' It also defines the record shape and explicitly states a non-goal: 'cannot look up a specific model,' which distinguishes it from lookup-oriented 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?

It provides clear context: use when you need a random sample, and it explicitly says there is no search parameter, telling the agent when not to use it. However, it does not name a specific alternative tool for lookups, so it stops short of full 5-level guidance.

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 behavioral disclosure burden. It transparently explains the random offset mechanism, that repeated calls return different aircraft, and that lookup by registration is not supported. This goes beyond the input schema and gives an agent realistic expectations.

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 three focused sentences: it states the operation, lists the record contents, and then clarifies sampling behavior and a key limitation. It is front-loaded with the core action and contains no 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 one-parameter tool with an output schema, the description provides all essential context: what is returned, how randomness works, and what the tool cannot do. Nothing critical is missing for correct invocation.

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 has 100% coverage for the single parameter, including range constraints (1 to 100). The description adds only the generic notion of sampling, which is already implied by the tool name and schema. Baseline 3 is appropriate because 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 opens with a specific verb and resource: 'Return a random sample of individual airplanes from the reference catalog.' It clearly distinguishes the tool from sibling random_aircraft_type by emphasizing individual airplane records and listing concrete fields, making the tool's purpose unambiguous.

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 states 'Sampling only: there is no lookup by registration,' which tells an agent when not to use the tool. It does not name sibling alternatives directly, but the sampling-only caveat provides clear usage boundaries.

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 behavioral disclosure burden. It usefully reveals that records come from a random offset and that repeated calls return different cities, but it does not specify edge behavior such as what happens if the requested sample size exceeds the catalog.

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 compact and front-loaded, putting the core purpose first and then adding behavior and boundaries. The field-enumeration sentence may partially overlap with the output schema, but it is not padded or verbose.

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 one-parameter sampling tool with a complete schema and an output schema, the description provides enough context: purpose, returned record fields, randomness behavior, and the no-lookup boundary. Nothing critical is missing for correct selection and invocation.

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%, and the schema already documents number_of_cities with type, range, and required status. The tool description adds no further parameter-specific meaning beyond the sampling context, so the baseline score of 3 applies.

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: 'Return a random sample of cities from the reference catalog.' The field list and the explicit 'no lookup by city name' boundary make it easy to distinguish from lookup and other random-catalog sibling 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 clearly frames the intended use as sampling and explicitly states a when-not condition: 'there is no lookup by city name.' It does not name specific sibling alternatives, so it stops short of full alternative routing.

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 discloses the random-offset mechanism, that repeated calls return different countries, and that the tool only samples rather than supports lookups. This gives an agent an accurate model of the tool's runtime behavior.

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 four sentences, each earning its place: purpose, output fields, randomness behavior, and the sampling-only limitation. It is front-loaded with the core action and avoids unnecessary elaboration or repetition.

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 single-parameter sampling tool with an output schema, the description adequately explains what records contain, how randomness works, and the tool's boundary. Nothing critical for selecting or invoking the tool is missing; an agent can confidently call it based on this definition.

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 input schema already provides 100% description coverage for the single parameter, including its range and meaning. The tool description does not add any extra parameter-specific semantics beyond what the schema states, so a baseline score of 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 opens with a specific verb and resource: 'Return a random sample of countries from the reference catalog.' It clearly distinguishes this tool from siblings that target cities, airports, aircraft, or flights, and the explicit 'Sampling only' statement reinforces that it is not a lookup tool.

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 states when to use the tool (when a random country sample is needed) and when not to use it: 'there is no lookup by country name or code.' This exclusion is clear enough to prevent an agent from calling it for deterministic retrieval, even without naming an alternative sibling.

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