MolTravel

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

With no annotations, the description bears full responsibility for behavioral disclosure. It states the lookup action (implying read-only) and code formats, but does not mention edge cases, return behavior, or any other operational details. It is not misleading, but minimal.

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?

A single, clear sentence that front-loads the purpose and directly specifies the accepted inputs. Every word contributes to the meaning, and there is no 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?

For a simple lookup tool with a single parameter, the description is sufficient. The purpose and input format are fully stated, and an output schema exists to cover return values. No additional context is necessary 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 0%, so the description must compensate. It does so by defining 'code' as an IATA (2-char) or ICAO (3-char) airline code, which is essential for correct parameter usage. This goes beyond the bare schema and gives the agent actionable format constraints.

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 action ('Look up an airline') and the specific resource, with precise input formats (IATA 2-char or ICAO 3-char). This differentiates it from airlines_search (which likely searches by name) and airports_lookup (which handles airports), making the 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?

There is no explicit guidance on when to use this tool versus airlines_search or other alternatives. The phrase 'by IATA or ICAO code' implies usage when a code is available, but no exclusions or alternative tools are mentioned.

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 a concrete behavioral limit ('Returns up to 20 results'), which is useful, but it does not disclose behavior like whether the 'active_only' filter is applied by default, sorting, or pagination.

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 very concise and front-loaded, using a single sentence with no filler. It is appropriately sized for a simple search tool, though it could have included a bit more parameter context without becoming 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?

Given the tool's moderate complexity (3 params, 1 required) and the presence of an output schema, the description covers the core search purpose and result limit. However, it omits the optional filtering parameters' behavior and offers no sibling differentiation, leaving some gaps for an agent deciding among similar 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 description coverage is 0%, so the description must compensate for explaining parameters. It only adds meaning to the 'query' parameter ('by name'), while the 'country' and 'active_only' parameters remain unexplained, leaving a significant semantic gap.

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 action ('Search') and the resource ('airlines'), with a specific filter ('by name'). It is precise but does not explicitly distinguish this tool from the sibling 'airlines_lookup', so it falls short of a perfect 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 provides no guidance on when to use this tool versus alternatives like 'airlines_lookup' or when to prefer other search tools. There is no mention of suitable contexts, prerequisites, or exclusions.

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 transparency burden. It discloses output behavior ('Returns full details including runways') and the required input format. The verb 'look up' implies a read-only operation, which is sufficient for a lookup tool. It does not mention error cases or permissions, but for a simple read operation this is acceptable.

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 short sentences, front-loaded with the core purpose. Every word adds value: the code formats, the return details, and the runway mention. No filler or 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 simple single-parameter lookup tool with an output schema, the description covers purpose, parameter format, and return characteristics. Sibling tool differentiation is inferable from the description, and no additional context is needed. It is complete for the tool's complexity.

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 fully compensates by explaining the 'code' parameter: it accepts IATA (3-char) or ICAO (4-char) codes. This adds critical meaning beyond the schema's bare 'string' type, making the parameter self-explanatory.

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 'Look up an airport by IATA (3-char) or ICAO (4-char) code', specifying the verb (look up), resource (airport), and exact input type. It distinguishes from sibling tools like airports_search and airports_near, which handle name-based or location-based lookups.

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 the use case: when you have an IATA or ICAO code, use this tool. It doesn't explicitly mention alternatives or exclusions, but the code-based scope gives clear context, and the sibling tool names (e.g., airports_search, airports_near) provide additional differentiation in context.

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. It adds 'Returns results sorted by distance,' which is a useful behavioral trait. However, it does not disclose default radius, limit handling, or the meaning of include_small, which could be relevant for agent decision-making.

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 one sentence of 13 words, front-loading the purpose with no redundancy. Every word earns its place, making it highly concise and well-structured.

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 5 parameters, no annotations, and no schema descriptions, the description is minimal. It covers the core function and sort order, but lacks explanations of the optional parameters (limit, radius_km, include_small) that could affect the output. An agent might struggle to correctly set include_small or understand the default radius. The presence of an output schema mitigates the need to describe return values, but the description remains incomplete.

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 mentions no parameters by name. It only vaguely references 'geographic point,' which maps to latitude/longitude but does not explain limit, radius_km, or include_small. The description adds no meaningful parameter information beyond what the schema already names.

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 ('Find') and resource ('airports') with a clear scope ('near a geographic point'), which distinguishes it from sibling tools like airports_lookup and airports_search. It also notes the sort order, making its function unmistakable.

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 a use case (finding airports near coordinates) but does not explicitly mention when to choose this tool over alternatives or any exclusions. The context is clear, but guidance on tool selection is only implied, not stated.

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 burden of behavioral disclosure. It reveals a 20-result cap and sorting by size, which is useful. But it does not clarify query matching behavior (exact vs. partial), case sensitivity, or possible error conditions. No contradiction with annotations exists since none are present.

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 a single, front-loaded sentence with no filler. It efficiently covers the core purpose and a key behavioral detail, making every word earn 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 simple search tool with three parameters and an output schema, the description provides a baseline of completeness: it clarifies search scope, result limit, and ordering. However, it omits semantics for optional filters and offers no comparative context with sibling tools. The output schema mitigates the need to describe return values.

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 compensate for all parameters. It only explains the 'query' parameter as searching by name or city. The optional 'country' and 'type_filter' parameters are completely unexplained, leaving their accepted values and purpose ambiguous.

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 'Search airports by name or city,' specifying a concrete verb and resource. It also adds scope details (returns up to 20 results sorted by size) that distinguish it from sibling tools like airports_lookup (likely exact code lookup) and airports_near (geographic search).

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 intended use is implied: use this when you need to find airports by name or city. However, there is no explicit guidance on when NOT to use it, alternatives such as airports_lookup or airports_near are not mentioned, and no prerequisites or exclusions are stated.

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. 'Check' implies a read-only operation, but the description does not disclose potential caveats such as what happens if datasets are not loaded or whether there are any side effects. It is adequate but minimal.

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 one concise sentence, front-loaded with the verb, with no wasted words. It efficiently communicates the tool's purpose.

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 simplicity (no parameters, output schema exists), the description is sufficiently complete. It lists the relevant datasets and what to expect (row counts), though it could optionally mention the meaning of 'loaded'.

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 tool takes no parameters (schema coverage 100% with empty properties), so there is nothing to explain. Per the rubric, a baseline of 4 is appropriate when there are zero parameters.

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 function: checking which static datasets (airports, airlines, visas) are loaded and their row counts. The verb 'Check' is specific, and the resource is well-defined, distinguishing it from sibling lookup/search 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 implies usage context (checking data availability) but does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or prerequisites. For a simple status check, the guidance is sufficient but not explicit.

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 accurately indicates a read-only list operation with no side effects, but adds no further behavioral context such as data completeness, ordering, or response details. This is adequate for a zero-parameter list tool 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 a single, front-loaded sentence with no redundant words. It efficiently communicates the tool's scope and action without any filler, earning a top score for conciseness.

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 list tool with no parameters and an output schema present, the description sufficiently defines the tool's scope ('all countries with UK FCDO travel advice'). It provides the necessary context for an agent to decide when to invoke this tool and what 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?

The input schema has zero parameters, so there are no parameter meanings to clarify. Baseline of 4 applies for zero-parameter tools, and the description adds no irrelevant parameter information.

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?

Description uses a specific verb ('List') and resource ('all countries with UK FCDO travel advice'), clearly distinguishing it from sibling fcdo_travel_advice which likely provides per-country details. The purpose is immediately obvious and actionable.

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 use when a list of all FCDO-covered countries is needed, but does not explicitly state when to use it versus alternatives like fcdo_travel_advice. No exclusions or alternative mentions are provided, leaving usage to inference.

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 must carry the transparency burden. It adds useful context by listing what the advice includes (safety, entry requirements, health, warnings), but does not disclose whether authentication is needed, data freshness, or any potential side effects. The tool appears read-only, but this is not explicitly stated.

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 a single, efficient sentence that front-loads the tool's identity and lists key contents without redundancy. The '[fcdo]' prefix adds context without wasting space.

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 tool is simple (one parameter, output schema exists), but the description does not explain how to obtain a valid country name (e.g., via 'fcdo_list_countries') or how it relates to overlapping tools like 'visa_check'. While the content list helps, this leaves some gaps in the broader context.

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 no description for the 'country' parameter (0% coverage), and the tool description only repeats 'specific country' without specifying the expected format (e.g., name vs ISO code) or giving an example. This leaves the agent guessing about how to supply valid input.

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 a specific verb ('Get') and resource ('UK FCDO travel advice') with scope ('for a specific country') and lists key content areas (safety, entry requirements, health, warnings). It naturally distinguishes from the sibling tool 'fcdo_list_countries' by focusing on a single country rather than listing all.

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 phrase 'for a specific country' implies when to use, but there is no explicit comparison to alternatives such as 'visa_check' or 'restcountries_country_info', nor any guidance on when not to use. Usage context is implicit, not differentiated.

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 states 'Get a list' which implies a read operation, but does not disclose return format, handling of no matches, directionality of connections, or any other behavioral details. The phrase 'all the direct connections' is ambiguous without mentioning the required portLocation parameter.

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 a single sentence with no wasted words, front-loading the tool name prefix. It is concise and structured acceptably, though it could include more useful context without becoming 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 tool with no annotations or output schema, the description is incomplete. It does not explain what 'direct connections' means, how the portLocation parameter affects results, or what the response contains. It leaves the agent to rely entirely on the schema and tool name, which is insufficient for effective tool selection.

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% with a clear description of portLocation ('Location name or search term used to find matching ports (not limited to exact port codes).'). The description adds no additional parameter semantics, but since the schema does the heavy lifting, the 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 clearly states the tool returns a list of direct connections between ports, using a specific verb and resource. It is distinguishable from sibling tools like ferryhopper_get_ports (returns ports) and ferryhopper_search_trips (searches trips), though it does not explicitly mention the filtering by portLocation.

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 does not reference sibling tools or mention exclusions, such as using ferryhopper_search_trips for indirect routes. The tool name implies usage for direct connections, but no explicit context is given.

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 full burden for disclosing behavioral traits. It only states that it fetches a list, but does not mention return format, pagination, data completeness, or whether the absence of disruptions returns an empty list. This is minimal disclosure for a read 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 a single, front-loaded sentence in the format '[tool] action resource with filters.' It contains no filler and all information is directly relevant. Excellent conciseness.

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 simplicity, the description covers the basic purpose and parameters, but lacks detail about the nature of disruptions or the output structure. Since there is no output schema, a brief note on return value would improve completeness. It is adequate but not rich.

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%: both parameters (tripDate and country) are described with format and examples. The description repeats the parameter roles without adding additional semantic value beyond what the schema already provides. Baseline 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 uses the specific verb 'Get' with a clear resource ('disruptions') and scoping ('for a given date and country'). This clearly states what the tool does and distinguishes it from sibling ferryhopper tools, none of which handle disruptions.

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 the usage context (date and country filtering) but provides no explicit guidance on when to choose this tool over alternatives, nor any exclusions or prerequisites. It is a functional statement without comparative 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 full burden of behavioral disclosure. It only states the action ('Get a list...') without revealing any behavioral traits such as read-only nature, static versus dynamic data, rate limits, or response characteristics. For a zero-parameter tool, a reader may infer it is a simple read operation, but this is implicit rather than explicit.

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 a single, concise sentence that is front-loaded with the action. Every word is meaningful: 'Get a list of global ports and their details' conveys purpose and scope without redundancy or unnecessary detail.

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 list tool with no output schema, the description is fairly complete but could be more helpful. It states the result (list of ports and details) but does not specify what 'details' means or how this fits into a workflow, such as using port IDs for subsequent ferry searches. Given the tool's simplicity, the description is minimally viable but leaves room for more context.

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 tool has zero parameters and no schema properties, so the baseline for parameter semantics is 4. The description adds the concept of 'global' scope, implying no filtering is required. It does not need to explain parameters since there are none, and the description accurately reflects that.

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 gets a list of global ports and their details, with a specific verb ('Get') and resource ('ports'). It distinguishes itself from sibling ferryhopper tools like ferryhopper_get_disruptions or ferryhopper_get_direct_connections_for_ports, though it does not explicitly compare to them. The phrase 'global ports' adds scope, making the purpose understandable.

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?

No guidance is provided on when to use this tool versus alternatives. The description neither mentions when to use it (e.g., before searching for direct connections) nor when not to use it. Sibling tools exist that could be alternatives, but no usage context or exclusions are offered.

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 of behavioral disclosure. It only adds 'available' and 'between two ports', but does not disclose output shape, whether trips are direct or connecting, sorting, empty results, or error behavior. This is under-specified for a tool with no annotation support.

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 one sentence with no filler; the '[ferryhopper]' prefix is a minor tag but does not hurt. Every remaining word contributes to conveying the tool's purpose and scope.

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?

With no output schema and no annotations, this minimal description leaves significant gaps: the agent cannot tell what a returned trip contains, how availability is determined, or how this tool relates to ferryhopper_get_direct_connections_for_ports. The schema covers inputs well, but the overall definition is incomplete for safe 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?

All three parameters are fully described in the schema with format and semantic notes (e.g., human-readable names, ISO date). The description adds little beyond restating 'between two ports on a specific date', so it meets the baseline for high schema coverage without adding extra meaning.

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 ('get a list available ferry trips') and resource ('between two ports on a specific date'), making the core purpose clear. However, it does not explicitly distinguish this from sibling ferryhopper_get_direct_connections_for_ports, which could be confused with trip search.

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 you need ferry trips between two ports for a specific date. It provides no explicit guidance on when to use this tool instead of ferryhopper_get_direct_connections_for_ports or other ferryhopper tools, nor any exclusions.

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 must shoulder the burden of disclosing behavioral traits. It only says 'Get', which implies a read operation, but does not explicitly confirm that it has no side effects, nor does it mention authentication requirements, rate limits, or any constraints. This lack of transparency is a notable 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?

The description is a single, front-loaded sentence that immediately conveys the tool's purpose without any filler. Every word earns its place, making it exceptionally concise and well-structured.

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 absence of an output schema, the description should compensate by explaining the nature of the return value. It only vaguely mentions 'dates, times, and pricing' without describing the structure (e.g., whether it returns a list, a calendar, or a single availability object). The tool has four required parameters and moderate complexity, so the description is insufficiently 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 input schema has 100% description coverage for all four parameters, so the baseline is 3. The description adds minimal value by tying the 'specific experience' to the id parameter and hinting at dates/times/pricing, but it does not enrich the meaning of 'quantity' or the date range semantics 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 clearly states a specific verb ('Get') and resource ('availability information for a specific experience'), and further specifies the content ('dates, times, and pricing'). It distinguishes from sibling tools like peek_experience_details or peek_search_experiences by focusing on availability.

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 the tool is for when you already have a specific experience ID and need availability, which provides clear context. However, it does not explicitly mention when not to use it or name alternative tools, so it stops 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?

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It does not state whether the operation is read-only (though 'peek' hints at it), what happens if the ID is not found, whether authentication is required, or any error behavior. The description is purely functional and lacks these contextual details.

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 a single, well-structured sentence that immediately states the action and target. It is front-loaded with the tool category marker '[peek]' and avoids any redundant wording. Every element earns its place, and there is 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 simple get-by-ID tool with one parameter and no output schema, the description is mostly adequate but leaves some gaps. It does not describe the returned data structure or handle cases like invalid/missing IDs. Given the simplicity and strong schema coverage, it is minimally viable but could mention expected output or error behavior to be more self-contained.

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 provides 100% coverage: the only parameter ('id') has a clear description ('The ID of the experience to retrieve'). The description adds no additional meaning beyond the schema, so the baseline of 3 is appropriate. No extra syntax or formatting is needed for a single string ID.

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 ('Get') and clearly identifies the resource ('detailed information about a specific experience') and the selection criterion ('by ID'). It naturally distinguishes itself from sibling tools like peek_search_experiences, which are for broader searches, making it immediately clear this is a singular retrieval 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?

The description clearly implies the use case: when you have a specific experience ID and need detailed information. It does not explicitly mention alternative tools or exclusions, but the context (search returns lists, this returns one item) is strong enough for an agent to infer appropriate usage. A minor gap is the lack of an explicit 'use this when you have an ID' statement.

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 must carry the transparency burden. It clearly implies a read-only, side-effect-free behavior through the word 'list', but it does not disclose output format, ordering, or any limits. For a zero-parameter tool this is minimally adequate but not rich.

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 one short sentence, front-loaded with the action and resource, and contains no filler 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?

The tool is extremely simple: no parameters, no annotations, and no output schema. The description conveys the essential behavior and is probably sufficient for a list-all operation, but it could clarify the exact shape or naming of the returned category tags, leaving a small gap.

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 has zero properties, so the baseline is 4. There are no parameter semantics to explain, and the description does not need to add input-related meaning beyond what the empty schema already shows.

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 the specific verb 'list' and identifies a clear resource: 'all category tags'. The '[peek]' prefix situates it within the Peek tool family, and it is distinct from sibling tools like peek_search_experiences because it enumerates a fixed taxonomy instead of searching.

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?

No guidance is provided about when to use this tool versus alternatives. The description only states the action and does not mention a context, prerequisite, or the typical workflow (e.g., using tags to filter experience searches), nor does it name any alternative tool.

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?

Since no annotations are provided, the description carries the full burden. It conveys the core operation (rendering) and output type (widget URI), implying a read-only, non-destructive action. However, it does not explicitly state whether modifications occur, error handling, or any side effects, so transparency is adequate but not rich.

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 a single, well-structured sentence that front-loads the [peek] tag, states the action, and specifies the return value. There is no 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 simplicity (one parameter, no output schema, no annotations), the description covers the essential purpose and output. It could explicitly mention that this is a read-only rendering action or add a note about valid ID requirements, but the core functionality is sufficiently described.

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 fully documents the only parameter 'id' with a description. The tool description adds no additional semantic value beyond repeating 'list of activity IDs', which matches the schema. Per the baseline rule, a 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 clearly states the tool renders activity tiles for a list of activity IDs and returns an embeddable widget URI. It uses a specific verb and resource, distinguishing it from sibling tools like peek_experience_details or peek_search_experiences.

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 you have activity IDs and need a widget URI, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. No alternative tools are mentioned.

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 returns categories, tags, and regions with IDs, which adds context about the output shape. However, it doesn't mention whether it's read-only, pagination behavior, or other side effects beyond 'search', which is generally safe but not explicitly stated.

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, front-loaded with the core action. The second sentence adds valuable detail about the return value without redundancy or fluff.

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 rich parameter descriptions and the absence of an output schema, the description sufficiently outlines purpose and output highlights. It could mention the actual list of experiences returned and any result format details, but the 'returns categories, tags, and regions' hint provides useful context for a search tool. This is a minor gap for a 7-parameter tool with no output schema.

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 each of the 7 parameters has a detailed explanation with usage examples. The tool description itself adds no parameter-specific meaning, but since the schema is thorough, 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?

The description clearly states it 'Search[es] for travel experiences' and specifically notes it returns categories, tags, and regions with IDs for further filtering. This distinguishes it from sibling tools like peek_experience_availability and peek_search_regions by naming the main search functionality and its filtering-oriented metadata output.

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 it is the main search tool with 'comprehensive filtering options' but does not explicitly name alternatives or state when-not-to-use. However, parameter descriptions within the schema (e.g., latLng's 'Don't use this for regions, instead use the search_regions') provide some guidance, though that is not part of the description itself.

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 gives only the basic search behavior. It does not disclose pagination (though schema has limit), result structure, sorting, or any side effects. This is insufficient for a tool with no safety 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 a single sentence that is front-loaded and free of filler. Every word contributes to the core purpose.

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 simple schema and no output schema, the description is minimally acceptable but lacks usage context or return-value expectations. An agent could use it, but might not know what regions are relevant or how results are returned.

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 fully describes both parameters (query and limit) with 100% coverage. The description adds no additional parameter-level meaning, 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 'Search for regions by name' clearly identifies the action (search) and resource (regions) with a name-based filter. It is distinct from sibling tools like peek_search_experiences, but it does not explicitly state that distinction.

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?

There is no mention of when to use this tool versus alternatives such as peek_search_experiences or other search tools. The description provides no context for selection, leaving the agent to infer from the name alone.

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 does not disclose behavioral traits such as whether it is read-only, any limitations, or output specifics. The word 'look up' implies a safe read operation, but this is not explicit.

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 a single sentence with no filler words, front-loading the core purpose. It is as concise as possible, though this brevity comes at the cost of missing context.

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?

With three parameters, no annotations, and no schema descriptions, the description is insufficient for an agent to construct a valid query. The existence of an output schema does not address input ambiguity.

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 0% description coverage, leaving query, fields, and search_by without explanations. The tool description does not compensate, offering no details on parameter formats, allowed values, or relationships.

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 action ('Look up') and resource ('country information'), and names the data source 'REST Countries', which gives it a specific meaning. However, it does not explicitly differentiate it from sibling tools like fcdo_list_countries, though the API reference helps.

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?

There is no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description is purely declarative and does not address usage context.

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 does mention the key output ('prices, companies, and car details'), indicating a read-only search. However, it does not disclose any other behavioral traits such as pagination behavior, default dropoff location, or potential limitations. A score of 3 reflects that some useful behavioral context is given but not rich.

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 a single sentence that is appropriately front-loaded with the tool purpose and returns. It is concise with no wasted words, making it easy to parse and understand quickly.

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 search tool with 9 parameters and no output schema, the description covers the core purpose and return value at a high level. It doesn't explain return structure or all parameters, but the schema already documents them. The description is sufficient for a straightforward search tool, though it could note pagination or defaults, so it earns a 4 rather than a 5.

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 vaguely references 'pickup and dropoff locations/dates', which aligns with the core parameters, but it adds no additional meaning beyond what the schema already provides. There is no extra detail on limit, offset, or location formats, so it does not surpass the baseline.

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 function with a specific verb ('Search'), resource ('Skiplagged for rental cars'), and the key inputs and outputs ('between pickup and dropoff locations/dates, returning prices, companies, and car details'). It distinguishes the tool from sibling tools that handle flights or hotels, making its 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 implies when to use this tool: when searching for rental cars. It provides clear context and the input types ('pickup and dropoff locations/dates'). However, it does not explicitly mention alternatives or exclusions, 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?

No annotations are provided, so the description carries the full burden. It implies a read-only search operation ('Find') and introduces the concept of cheapest destinations, but it does not disclose result format, how many destinations are returned, whether round-trip vs one-way affects results, or any limitations. It adds basic behavioral context but lacks depth.

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 sentences, front-loaded with the action and purpose. The second sentence adds a helpful nudge ('Perfect for discovering travel opportunities and deals') without fluff 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?

This is a complex tool with 9 parameters, no annotations, and no output schema. The description explains the core use case but does not cover expected return values (e.g., list of destinations with prices), how optional parameters like return date or fare_class influence results, or any edge cases. While the schema covers parameters well, the description leaves the tool's output behavior largely unstated.

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 provides 100% description coverage for all 9 parameters, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already provides, beyond contextualizing 'from' as a departure city and the flexible-destination intent. It does not compensate for any gaps since there are none in 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?

The description clearly states the tool's purpose: 'Find cheapest destinations from a departure city when flexible about where to go.' This uses a specific verb (Find) and resource (cheapest destinations) and distinguishes it from sibling tools like skiplagged_sk_flights_search (specific flights) and skiplagged_sk_hotels_search.

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 phrase 'when flexible about where to go' gives clear usage context, implying this is for destination-flexible searches rather than specific destination searches. It doesn't explicitly name alternative tools or exclusions, but the context is unambiguous enough for most use cases.

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. It implies a read-only search operation but doesn't disclose return format, pagination, or any limitations beyond the schema. The description adds scope (company, stuff, products, policies) but lacks deeper behavioral details.

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 a single, front-loaded sentence with no wasted words. The '[skiplagged]' prefix adds context, and every phrase contributes to understanding the tool's purpose and usage.

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 tool is simple, and the description covers its purpose and use case. However, without an output schema, it doesn't specify the return format (e.g., list of articles, snippets, URLs). It's fairly complete for a straightforward search tool, but not exhaustive.

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 each parameter (query, top_k, renderMode) already described. The description doesn't add parameter-specific meaning beyond the schema, so the baseline 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 clearly states the tool's function: 'Search FAQ for relevant answers about Skiplagged' with a specific verb and resource. It distinguishes itself from sibling tools by targeting FAQ retrieval specifically, unlike flight/hotel/car search 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 for when to use the tool: 'Useful for customer support and general inquiries.' It doesn't explicitly state when not to use it, but the context is well-defined and differentiates it from other Skiplagged search tools.

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 must carry the behavioral burden. It discloses that it returns one-way fare calendars around a departure date and highlights lowest prices. However, it does not describe how the 'around' range is determined, whether returnDate is supported despite saying 'one-way', or any other edge behaviors. This is adequate but leaves notable gaps.

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, front-loaded with the core action, and no redundant wording. Every phrase adds relevant context: the tool's purpose, output type, and intended use.

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 10 parameters, no annotations, and no output schema, the description provides a solid high-level picture: what it does, what it returns, and when to use it. It lacks finer details (e.g., how many days in the calendar, behavior with returnDate), but for tool selection and invocation it is largely sufficient. A score of 4 reflects good coverage without being exhaustive.

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 the 'one-way' qualifier, which clarifies the departureDate semantics somewhat, but it does not elaborate on other parameters like sort, passengers, or renderMode. It neither compensates for nor conflicts with the schema, so the baseline 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?

Description uses a specific verb ('Generate') and resource ('flexible calendar of the lowest one-way fares'), and clearly states the output format (date → cheapest-price entries). It also distinguishes from sibling tools by explicitly noting 'one-way' and 'flexible-date price discovery', separating it from exact itinerary search tools like skiplagged_sk_flights_search and the return-calendar 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 states intended use: 'Intended for flexible-date price discovery, not exact itinerary selection.' This tells the agent when to use this tool versus alternatives. While it doesn't name sibling tools directly, the exclusion of exact selection is clear and actionable.

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. It discloses the return format (depart date, return date, lowest total price), the nature of results (nearby date pairs preserving trip length), and clearly states it is not for exact itinerary selection, implying it is a read-only search tool. It does not mention data freshness, rate limits, or whether results are live, but for a price calendar tool this is sufficient and adds meaningful behavioral context beyond the schema.

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 sentences, each earning its place: the first states the core function, the second details the output and purpose. There is no redundant or filler content, making it appropriately concise and 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?

Given the tool's complexity (10 params, no output schema), the description provides sufficient context by explaining the return entry structure and clarifying the tool's scope (price discovery). The schema handles individual parameter documentation, and the description covers the high-level behavior and output. It could mention result limits or the effect of passenger counts, but these are secondary and covered by schema defaults.

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 baseline is 3. The description adds semantic value by explaining the relationship between departureDate and returnDate: a 'fixed-length stay' and 'nearby date pairs that preserve the original trip length.' This clarifies how the date parameters interact, which is not evident from the individual schema descriptions alone.

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 a specific action: 'Generate a flexible round-trip price calendar for a fixed-length stay around a chosen travel window.' It also distinguishes from the sibling tool 'skiplagged_sk_flex_departure_calendar' by emphasizing round-trip and the combination of depart/return date pairs, returning (depart date, return date, lowest total price).

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 a clear context: it is for price discovery, not exact itinerary selection. It implies use when exploring flexible round-trip options around a travel window. However, it does not explicitly name alternatives like 'skiplagged_sk_flights_search' for exact dates or 'skiplagged_sk_flex_departure_calendar' for one-way flexibility, so it lacks explicit when-not/alternative guidance beyond the 'not exact itinerary selection' caveat.

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?

Annotations are absent, so the description carries the full burden. It only summarizes the search function and filter options, but doesn't disclose read-only nature, output format, pagination behavior, or any limitations. It does not contradict annotations because none exist.

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?

One sentence, front-loaded with the action and resource, no filler. However, it omits important details for such a complex tool, so it's concise but under-specified.

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?

With 27 parameters and no output schema, the description is too sparse. It doesn't explain what the response contains (e.g., pricing, duration, airlines) or any caveats, leaving the agent to infer from the tool name.

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 93%, so the schema already documents parameters in detail. The description adds broad categories like 'passengers, fare class, stops, airlines, and timing' but no specific meaning beyond what the schema 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 clearly states it 'Search Skiplagged for flights between specific locations' and lists filtering categories. This distinguishes it from car/hotel search tools, though it doesn't explicitly differentiate from the flex calendar 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?

No guidance is provided on when to use this tool versus alternatives like flex_departure_calendar or other flight search tools. No exclusions, prerequisites, or contextual triggers are mentioned.

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 transparency burden. It clearly states the operation is a fetch (read) of availability, pricing, and amenities, but does not disclose caching behavior (live vs cached), rate limits, or potential error conditions. It adds basic transparency but no deeper behavioral context beyond what the schema's 'live' parameter hints at.

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 a single, focused sentence that front-loads the action ('Fetch') and the resource details. It is free of filler words and the '[skiplagged]' prefix efficiently establishes the provider context.

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 8 parameters and no output schema, the description provides the core purpose but omits workflow context such as the need to first obtain a hotelId from skiplagged_sk_hotels_search. It also does not elaborate on the output structure beyond naming availability, pricing, and amenities. Adequate but with identifiable gaps.

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 not add any parameter-specific meaning beyond the schema; it only references 'specific hotel and stay dates,' which maps to the required parameters (hotelId, checkin, checkout). No extra guidance is provided for optional parameters like numRooms or live.

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 the specific verb 'Fetch' and clearly identifies the resource as 'room-level availability, pricing, and amenities for a specific hotel and stay dates.' This precisely distinguishes it from sibling search tools like skiplagged_sk_hotels_search or flight/car search 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 phrase 'for a specific hotel' implies the tool is used after selecting a hotel from search results, but it does not explicitly state when to use this tool versus alternatives like skiplagged_sk_hotels_search. No alternatives or exclusions are mentioned, leaving usage guidance partially implied.

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 only mentions that ratings and pricing are included, but does not disclose output format, pagination behavior, rate limits, or any limitations. This leaves significant behavioral aspects undocumented.

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 a single, succinct sentence that front-loads the tool name and action. It conveys the core purpose without unnecessary words, making it highly efficient.

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 has 10 parameters and no output schema, the description is too minimal to provide complete context. It does not explain return structure, pagination, or how results are organized, and it does not mention any important caveats about the search. An agent would have limited guidance for using this tool beyond the raw schema.

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 description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond restating check-in and check-out dates; it does not clarify parameter relationships, defaults, or options like sort or limit beyond what the schema already documents.

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 searches Skiplagged for hotels in a city with specific dates, and mentions that results include ratings and pricing. This distinguishes it from sibling tools like skiplagged_sk_hotel_details (which focuses on a specific hotel) and skiplagged_sk_cars_search (cars), 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 implies usage for hotel search with check-in/check-out dates, but it does not explicitly state when to use this tool over alternatives like trivago accommodation search or skiplagged_sk_hotel_details. No exclusions or alternative recommendations are provided, so the guidance is only implicit.

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 but only states the core action. It does not describe what happens for invalid city names, whether multiple results can be returned, or the output format, leaving significant behavioral ambiguity.

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 a single, front-loaded sentence with no redundant words. It efficiently communicates the tool's purpose without any 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?

The tool is simple with only two well-documented parameters and no output schema, so the description gives the necessary core purpose. However, it does not clarify the exact input format (e.g., whether 'city name' means 'New York' or 'JFK') or what output to expect, leaving some gaps for an agent using the tool autonomously.

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 descriptions for both parameters, achieving 100% coverage. The description adds no extra parameter meaning and even introduces slight ambiguity by saying 'city name' while the schema says 'City name code', but the baseline of 3 applies given the 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 uses a specific verb 'Resolve' with a clear resource 'city name to a valid IATA code', making the tool's purpose unambiguous. It distinguishes itself naturally from related siblings like 'skiplagged_sk_resolve_location' by focusing on IATA code resolution.

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 usage context is implied: the tool is for converting a city name into a valid IATA code. However, there is no explicit mention of when to use this tool versus the similar 'skiplagged_sk_resolve_location' or airport lookup tools, and no alternatives or exclusions are provided.

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 states the core function but does not mention return format, what 'nearest' is based on, error handling for invalid coordinates, or whether it returns multiple airports. For a simple geo-resolution tool, this is adequate but not rich; more context about output would be useful.

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 a single sentence that is front-loaded with the '[skiplagged]' tag and immediately states the purpose. It contains no filler, every word contributes value, and it is appropriately sized for the tool's simplicity. This is exemplary conciseness.

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 simplicity (two required numeric parameters, no output schema), the description captures the core function well. However, it does not specify what 'city information' includes (e.g., city name, country, etc.) or the structure of the return value, which could leave an agent uncertain about the response. There is no mention of edge cases or limitations, so completeness is adequate but not thorough.

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 covers all parameters (lat, lng, renderMode) with brief descriptions, and schema coverage is 100%. The tool description adds context that 'lat' and 'lng' are used to find the nearest airport, which is beyond the schema's bare 'latitude' and 'longitude'. However, it doesn't explain renderMode further or any parameter constraints, so it does not significantly elevate the semantic meaning 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?

The description clearly states the tool's function: 'Resolve latitude and longitude to the IATA code of nearest airport and city information.' It uses a specific verb ('Resolve') and resource (lat/lng to IATA), and implicitly distinguishes itself from the sibling tool skiplagged_sk_resolve_iata, which does the reverse. This is a clear and unambiguous purpose.

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 you have latitude/longitude and want the nearest airport IATA code and city info, use this tool. However, it does not explicitly state when not to use it or mention alternatives such as skiplagged_sk_resolve_iata (for IATA to coordinates) or airports_near. This makes the guidance merely implied, not explicit.

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 burden of disclosing behavior. It states that the tool searches by name and returns matching operator IDs, which covers the basic read-only nature. However, it omits details like whether the search is exact/partial, how many results are returned, or what happens if no match is found.

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, front-loaded with the usage scenario and directly followed by the operational detail. Every sentence adds value with no 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 simple one-parameter search tool with no annotations or output schema, the description provides adequate context: what it does, when to use it, what it returns, and how to use the result. It lacks some edge-case behavior (e.g., partial matches, result limits) but is largely complete for its complexity.

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 already fully documents the textSearch parameter with an example. The description adds context about the returned ID being used for tour filtering, but no new parameter-level semantics. Given 100% schema coverage, the baseline 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 clearly states the tool's purpose: finding a tour operator's ID by name for filtering tours. It uses a specific verb ('find') and resource ('tour operator's ID'), and the context of 'filtering tours' distinguishes it from other tourradar search 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 explicitly states when to use the tool ('Use this when you need to find a tour operator's ID'), but does not mention when not to use it or provide explicit alternatives. The phrase 'for filtering tours' implies the alternative of searching tours directly, but this is not stated.

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. It discloses support for multiple name variants (e.g., Krakow, Kraków, Cracow) which is helpful, but it does not describe search matching behavior, return format, or potential edge cases like no results.

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 sentences long, front-loaded with the primary use case, and contains no redundant or filler content. Every sentence contributes meaningful 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?

For a simple 2-parameter lookup tool, the description covers the core purpose and usage context adequately. It could improve by mentioning the expected output structure, but the absence of an output schema makes this less critical.

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 search parameter already provides detailed guidance including examples of passing name variants. The tool description adds minimal new parameter information beyond what the schema already states.

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 function: 'Searches for cities by name within a specific country' and explicitly ties it to finding city IDs for tour filter fields like start city, end city, or cities to visit. This specificity distinguishes it from sibling tour search 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 opening sentence gives explicit usage guidance: 'Use this when you need to find city IDs for tour search filters...' It does not name alternatives, but the use case is clear enough to guide selection.

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 burden of disclosing behavior. It accurately describes a read-only list operation and mentions the output fields (IDs and names). However, it does not mention any limitation, auth requirements, or data format details, which are minimal for a simple list but still a slight 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?

The description is exceptionally concise: two short sentences with no filler. It front-loads the usage guidance and then states the output, making it easy to parse quickly.

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 no-parameter list tool, the description fully covers what it does, when to use it, and what it returns. There is no output schema, but the description explicitly lists the return content (IDs and names), making it 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 tool has zero parameters, so the baseline is 4. The description adds context by noting the output is intended for use in tour search filters, which gives semantic meaning even without parameters.

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 returns a list of supported continents with their IDs and names. It uses a specific verb ('Returns') and identifies the resource (continents list), distinguishing it from sibling tools like countries-list or cities-search.

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 'Use this when you need continent IDs for filtering tours by region,' providing clear usage context. It does not explicitly mention when not to use it or alternative tools, but the context is sufficient for this simple lookup tool.

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 of behavioral disclosure. It clearly states that the tool returns a complete list with IDs, names, and ISO codes, which effectively communicates the read-only, informational nature. It does not mention potential pagination or data freshness limitations, but for a simple list endpoint this is adequate.

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 short sentences, front-loaded with the use case and followed by a concise description of the return value. Every word adds value, with 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 parameterless, list-returning tool, this description is complete. It covers the purpose, the trigger conditions, and the exact shape of the returned data (IDs, names, ISO codes). No output schema exists, but the description supplies the essential return information.

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 tool has zero parameters, so the description doesn't need to explain parameters. It does add context about the output fields (IDs, names, ISO codes) which is useful beyond the empty input schema. This aligns with the baseline for no-parameter tools.

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: looking up country IDs and validating country names. The verb 'look up' plus the resource 'country IDs' is specific, and the mention of returning a country list distinguishes it from other lookup/list 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 explicitly says when to use the tool ('when you need to look up country IDs for filtering tours or validating country names'). It does not provide explicit when-not-to-use instructions or alternatives, but the use case is clear and sufficiently targeted.

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 burden of disclosing behavior. It clearly states that it 'Returns a list of all supported currencies' with specific attributes, which implies a read-only, non-destructive operation. It doesn't mention rate limits or errors, but for a zero-parameter list, this is adequately 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?

The description is two sentences, front-loaded with the use case and immediately followed by the return value details. Every sentence adds value, with no 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?

For a zero-parameter, no-output-schema list tool, the description fully covers what the agent needs: when to use it and what to expect in the response (codes, names, symbols with examples). It is complete for its simplicity.

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 tool has zero parameters, and the schema is an empty object with 100% coverage. According to the rubric, zero-parameter tools get a baseline of 4. The description adds no parameter info because there are no parameters to describe, which 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 clearly states the tool's purpose: to check supported currencies and get currency details like symbols. It distinguishes itself from sibling list tools (cities, countries, languages) by its specific focus on currencies.

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 an explicit 'when to use' ("Use this when you need to check supported currencies or get currency details like symbols"), but does not mention alternatives or when not to use. For a simple list tool, this is sufficient guidance, but it lacks explicit exclusions.

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 must convey behavioral traits. It discloses that the tool returns a list with IDs, codes, and names, and implies the operation is read-only. However, it does not mention any additional behavior such as response format, pagination, or errors, but for a simple list endpoint this is adequate.

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 sentences: the first states when to use the tool, the second states its output. Every word is purposeful, with no redundancy or filler. It is front-loaded with the tool's key purpose.

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 tool is simple: no parameters, no output schema, and a straightforward listing purpose. The description fully explains why you would use it (to get language IDs for filtering) and what it returns (IDs, codes, names). This is complete given the tool's low complexity.

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 tool has zero parameters, so the baseline is 4. The description does not need to add parameter semantics, and the schema already confirms no parameters exist. The description adds no parameter information because none is needed.

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 returns a list of all supported languages with their IDs, codes, and names. It uses a specific verb ('Returns a list') and a specific resource ('supported languages'), and its purpose—supporting tour search filters—is unambiguous. It is clearly distinguished from sibling list tools by focusing on languages.

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 'Use this when you need language IDs for filtering tours by guide language,' giving a clear use case. It does not mention when not to use it or alternatives, but the context is sufficient for a simple lookup tool.

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?

Since annotations are absent, the description carries the full burden for behavioral disclosure. It only says 'fetches operator details,' implying a read-only operation, but it does not explicitly state that, nor does it mention any side effects, error behavior, or special requirements beyond an operator ID. This is a minimal disclosure for a tool with no annotation support.

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 sentences, front-loaded with the use case, and every sentence adds value. There is no fluff or repetition of schema details, making it appropriately concise and well-structured.

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 1-parameter tool with no output schema, the description covers the purpose, when to use, and gives a glimpse of the output fields ('name, code, and terms & conditions'). It is mostly complete, though it could mention edge cases (e.g., invalid operator ID) or explicitly confirm the read-only nature. Overall, it is sufficient for the tool's simplicity.

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 description adds meaning by saying fetch details are 'based on operator ID,' which clarifies the role of the sole parameter. However, with 0% schema description coverage, it does not fully compensate by explaining the ID format or its origin (e.g., from a search tool). It does list the returned details, giving some context, but the parameter semantics are only partially covered.

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 fetches operator details (name, code, terms & conditions) based on operator ID, using a specific verb ('fetches') and resource. It distinguishes itself from sibling tools like tourradar_algolia-operator-search, which is for searching operators, by focusing on retrieving details for a specific operator.

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 first sentence gives explicit usage context: 'Use this when the user wants information about a tour operator, such as their terms and policies.' This is clear, but it does not mention when not to use it or explicitly reference alternative tools, so it misses the full 'when-not' 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 burden. It discloses the return content (availability, pricing, booking info) but does not mention whether the operation is read-only, any permissions required, pagination behavior, or potential limitations. It is adequate but not rich.

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 concise: two sentences with the usage context front-loaded. Every sentence adds 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?

With no output schema, the description partially explains the return values (list of departures with availability, pricing, booking info). It covers the primary use case but omits pagination details and any edge-case behaviors, leaving minor gaps.

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?

All parameters have descriptions in the schema (100% coverage), so the baseline is 3. The tool description reinforces the use of tourId and dateRange but does not add new syntactic or format details beyond the schema. The page parameter is not mentioned in the 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 identifies the tool as returning a list of departures for a tour, with specific capabilities (availability status, pricing, booking info). It mentions a date range and distinguishes this from other tourradar tools like tour details, FAQs, or booking.

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 user asks about departure dates, pricing for specific dates, or validating availability. However, it does not explicitly name alternatives or provide 'when not to use' guidance, so it falls short of a perfect score.

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 implies a read-only operation via 'Fetches' and lists the output categories, but it omits prerequisites (e.g., where to obtain a valid tourId), error/not-found behavior, and any B2B-specific access constraints hinted at by the tool name.

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 short sentences, with the use case front-loaded and the content list concise. Every word earns its place; there is no filler 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?

For a simple fetch-by-ID tool, the description covers the main purpose and primary output categories. However, without an output schema and with only partial parameter documentation, it does not explain response structure, the optional currency parameter (though the schema covers it), or how to obtain a tourId, leaving some gaps for the agent.

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 only 50%; tourId has no description in the schema. The description merely restates 'based on tour ID' without adding guidance on how to find or validate a tour ID, while currency is already well-documented in the schema and receives no added context.

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 ('Fetches') and clearly identifies the resource ('comprehensive tour details' for a specific tour), listing key content categories (itinerary, pricing, operator info, images, booking links). This clearly distinguishes it from sibling tools such as tour-departures, tour-faq, or tour-map.

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 states 'Use this when the user wants to see detailed information about a specific tour,' providing clear context for when to invoke the tool. It does not name alternatives or exclusions, but the directive is unambiguous and sufficient for selection.

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 of behavioral disclosure. It mentions pagination ('paginated list') and the content coverage (inclusions, requirements, policies), which is helpful. However, it does not disclose authentication needs, error behavior, or response structure, which are relevant for an API 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 two sentences: a usage trigger and a result summary. No unnecessary details, front-loaded with the key use case. Very concise and well-structured.

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 simplicity (2 params, no output schema), the description covers the main aspects: when to use, what it returns (paginated FAQ list), and topic focus. It does not outline exact response fields, but that is not essential for this type of lookup tool. It is fairly complete for its context.

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 only 50% (page is described, but tourId is not). The description adds minimal semantic value for parameters: 'about a specific tour' implies tourId but does not explain it, and the page parameter is not mentioned at all. The description does not compensate for the missing schema 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 clearly states the tool returns a paginated list of frequently asked questions and answers about a specific tour. It uses a specific verb ('Returns') and a resource ('FAQ section'), and the context about user questions distinguishes it from sibling tools like tour details or departures.

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 an explicit when-to-use instruction: 'Use this when the user has questions about a tour that might be answered in the FAQ section.' It does not mention alternatives or exclusions, but the usage context is clear and actionable.

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 states that it 'fetches tour details' and 'prepares map data,' which implies a read-only operation but does not disclose details like output format, potential errors, or rate limits. The description adds some behavioral context but is 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 concise, with two sentences that are front-loaded with the use case. Every word serves a purpose; no filler 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?

The description gives a solid overview of the tool's behavior and output ('map data with all itinerary locations, coordinates, and day-by-day information'). While it lacks explicit output schema details, the description is adequate for an agent to understand what to expect and when to use it, especially given the simplicity of the tool.

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 50%, with only 'currency' documented. The description mentions 'one or more tours,' which aligns with the required 'tourIds' parameter, but it does not explicitly explain what tourIds are or how to provide them. Currency is described in the schema, and the description adds no extra meaning. Baseline of 3 is appropriate given the partial coverage and marginal additional context.

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 function: showing tour routes on a map and comparing itineraries visually. It uses specific language ('see tour routes on a map', 'compare itineraries visually') that distinguishes it from sibling tools like tour-details or tour-search which serve different purposes.

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 first sentence provides explicit guidance on when to use this tool: 'when the user wants to see tour routes on a map or compare itineraries visually.' This gives clear context, though it does not explicitly list when not to use it or name alternative tools.

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. It discloses the return structure as a hierarchical list of groups and types with IDs and names. For a simple read-only list tool, this is sufficient; it doesn't hint at side effects or errors, but none are expected.

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 sentences: the first gives an immediate usage directive, and the second succinctly summarizes the output. Every sentence earns its place, with no redundancy or fluff.

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 (0 params, no output schema), the description adequately covers purpose and return type. Minor gap: it doesn't specify whether the hierarchy is always full or if it can be filtered, but for a list tool this is sufficient.

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 tool has zero parameters, and the schema is empty. Per the baseline for 0-param tools, a score of 4 is appropriate. The description doesn't need to explain parameter semantics since there are none.

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 clear verb 'Returns' and specifies the resource: a hierarchical list of tour type groups with individual types, IDs, and names. This clearly distinguishes it from sibling list tools like continents-list or countries-list by focusing on tour types for filtering.

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 'Use this when you need tour type IDs for filtering tours by category' providing a clear trigger condition. It does not mention exclusions or alternatives, but the guidance is specific enough for an agent to select it for tour-type lookups.

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. It clearly states the output format (ISO) and action (returns current date/time). It does not mention timezone or that it is a safe read-only operation, but for a date utility this is quite 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?

Two sentences, front-loaded with the primary use case and output format. Every sentence adds value with no fluff.

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 utility tool with no output schema, the description fully covers purpose, usage, return format, and relevancy to tour searches. Nothing essential 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?

The tool has zero parameters, so no parameter explanation is needed. The baseline for 0 params is 4, and the description correctly avoids wasting space on parameter details.

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 clear action: 'Returns the current date and time in ISO format.' It identifies the resource (current date) and is distinct from sibling tools like tour search or booking tools. It also provides a specific use case context.

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 clear guidance on when to use: 'Use this when you need to know the current date, especially before setting departure date filters.' It does not mention alternatives, but there is no obvious alternative sibling for this simple utility, so the context is sufficient.

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. It discloses key behaviors: AI-powered semantic search, the requirement for tourIds, and the optional text query for topic filtering. It doesn't mention output format or pagination behavior, but for a read-only search tool this is adequate context. The note about combining with a query adds useful behavioral detail beyond structured fields.

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. The first sentence states the core purpose. Each subsequent sentence adds essential context: requirement, when to use, how to combine query, and fallback to sibling tools. No filler or repetition — every 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 an 8-parameter tool with no output schema, the description provides sufficient context: purpose, required scope, usage timing, and alternatives. It doesn't cover pagination or default sorting, but the schema fully documents parameters. The tool description is complete enough 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?

Schema coverage is 100%, so the baseline is 3. The description adds extra value by explaining that the query should be 'short natural language', providing concrete examples ('food', 'guide', 'accommodation'), and explicitly recommending the 'keywords' parameter when topics are known. This reinforces and clarifies the schema without being redundant.

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 tour reviews using AI-powered semantic search.' It specifies the resource (tour reviews), the action (search), and the key constraint (requires tourIds to scope results). This distinguishes it from sibling tools like vertex-tour-search and vertex-tour-title-search, which are explicitly named as alternatives for finding tours first.

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 explicit when-to-use guidance: 'Use this when the user asks about reviews, feedback, or experiences for specific tours.' It also gives clear alternatives: 'When you don't have tour IDs, use vertex-tour-search or vertex-tour-title-search first to find them.' This is strong, actionable usage context.

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 must carry the full transparency burden. It discloses that the tool uses Google Vertex AI to understand intent, supports semantic search, and returns a list of tours with ID, name, URL, operator, and description. It also mentions performance characteristics ('to make search faster') and covers display modes. However, it does not mention edge cases like empty results or error behavior, which slightly lowers the score from a 5.

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 well-structured with headings, tables, and examples, and it is front-loaded with usage guidance. However, it is quite long and repetitive, with filter details duplicated from the schema and multiple examples that could be condensed. Every sentence does not earn its place, so it is not a model of conciseness.

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 high complexity (19 parameters, nested objects, no output schema), the description is thorough: it covers the required `textSearch`, optional filters across location, range, and AND/OR categories, provides comprehensive examples, and describes the response format. It references auxiliary tools like `b2b-cities-search` for IDs and explains the display modes. Minor gaps (e.g., no mention of pagination or result limits) prevent a 5.

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 95%, so the schema already provides rich descriptions for most parameters, earning a baseline of 3. The description adds a consolidated filter table and examples that clarify usage (e.g., age range examples for family-friendly tours), but much of this duplicates schema text. It does not add substantial new semantics beyond the schema, so a 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 clearly states the tool performs AI-powered semantic search for tours using natural language queries with optional filters. It explicitly names the tool (`vertex-tour-search`) and distinguishes it from sibling tools like `tourradar_vertex-tour-title-search` and `tourradar_vertex-review-search` by focusing on natural-language intent understanding. The phrase 'Use `vertex-tour-search` when...' further reinforces its specific purpose.

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 explicit when-to-use guidance with bullet points ('Use `vertex-tour-search` when: the user describes what they want in natural language', etc.) and strongly encourages filter usage to improve speed and precision. It lacks explicit when-not-to-use or alternative tool references, but the context is clear enough for an agent to distinguish this from other search tools.

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 the semantic search nature and the return format (IDs and titles), which is useful. However, it doesn't mention any nuances like behavior on no matches, result ordering, or limits. This is adequate but not rich.

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 sentences, front-loaded with the core function, and includes a follow-up usage note about an alternative tool. Every sentence earns its place; there is no redundancy or fluff.

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 search tool, the description covers the purpose, output, and usage context, and points to an alternative. It doesn't have an output schema, but it does say what will be returned. Missing minor details like result count or ordering, but overall complete for the tool's complexity.

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% for the single parameter, and the schema describes it as 'Tour title or partial title to search for.' The description repeats 'by title' and doesn't add extra meaning beyond the schema, such as example formats or matching rules. The baseline of 3 applies because the schema already covers the 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 clearly states the tool's function: 'Search for tours by title using AI-powered semantic search' and specifies the output ('matching tour IDs and titles'). It distinguishes itself from the b2b-tour-details tool by explicitly pointing to the alternative when a tour ID is known, and the focus on title-based lookup differentiates it from other search 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 explicit when-to-use guidance: 'Use this when you need to look up a tour by name.' It also names an alternative for a different scenario: 'When you know tour id, use b2b-tour-details tool.' This is clear and actionable.

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 that no booking is created, that omitting departureDate lets the backend pick the nearest departure, and that user data must be real. However, it does not mention side effects like sending an inquiry to the operator, rate limits, or authentication requirements.

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 moderately long but well-structured: a purpose sentence, mode breakdown, and user-data rules. Every section is useful, and the bullet-like layout aids scanning, though it does repeat some schema 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 no output schema and no annotations, the description covers most necessary context: modes, required IDs, optional date behavior, and data integrity rules. The main gap is what the tool returns or confirms after sending the question, but for a submission-style tool this is not a critical omission.

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 describes all parameters (100% coverage), but the description adds valuable semantics: it clarifies the entity modes, explains that departureDate is optional and should not be fabricated, and emphasizes using real contact details. This goes beyond the schema's property descriptions.

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 explicitly states 'ASK A QUESTION about a tour or operator WITHOUT committing to a booking,' which names the verb (ask), resource (tour/operator), and constraint (no booking). This clearly distinguishes it from sibling tools like booking or search 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 opens with 'Use this when...' and details two modes (tour vs operator) with required IDs. It also includes exclusions ('WITHOUT committing to a booking') and data-handling rules, though it does not explicitly name alternative tools.

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 must carry the burden of behavioral disclosure. It goes beyond the basic action by emphasizing that real contact details are required, that the agent must never fabricate or assume user data, and that missing information should be asked for. This adds valuable operational constraints beyond the schema, though it does not describe post-creation behavior or side effects.

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, front-loaded with the usage condition, and every sentence adds necessary context: action, prerequisites, confirmation step, and anti-fabrication warning. No wasted words.

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 write tool with 10 parameters and no output schema, the description covers when to use, required data, a critical prerequisite (check departures), and behavioral guardrails. It could be more explicit about the nature of a 'booking request' (e.g., that it's not a final booking), but overall it is quite complete for the given complexity.

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 high (80%), so the schema already documents most parameters. The description adds a general requirement for 'real contact details (email, names; phone optional)' and stresses to ask for missing info, which complements the schema but does not significantly add per-parameter semantics beyond what's already present.

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 action ('Creates a booking request') and the resource ('a specific tour'), and specifies the triggering condition ('when the user explicitly wants to book a tour and has provided their contact details'). This distinguishes it from sibling tools like tourradar_web-ask-question or tourradar_web-tour-send-brochure.

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 the user explicitly wants to book a tour and has provided their contact details') and provides a procedural guideline ('Always confirm the departure date by checking departures first'). It does not explicitly mention when not to use or name alternative tools, which keeps it just 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 provided, the description carries the full burden of behavioral disclosure. It does disclose that the tool sends a PDF and explicitly states a key behavioral constraint: never generate or assume email addresses, which adds useful context. However, it does not describe potential side effects such as what happens if the tourId is invalid, whether the email could fail, or what response/confirmation the user should expect. This is a moderate level of transparency, but gaps remain.

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 extremely concise and front-loaded. The first sentence immediately states the trigger condition, and the second paragraph provides the essential behavioral detail in two short sentences. There is no redundant or filler content. Every sentence earns its place, making it easy for an agent to parse quickly.

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 (2 parameters, no nested objects, no output schema) and the rich schema descriptions, the description provides a complete-enough picture for an agent to invoke it. It covers the purpose, the email collection workflow, and the action taken. However, it lacks information about what happens after sending (e.g., success confirmation or error handling), which would be helpful since there is no output schema to clarify return values.

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% coverage of both parameters with detailed descriptions: 'email' includes format, pattern, and instruction to ask the user if not provided; 'tourId' is described as required with constraints. The tool description adds little beyond reinforcing the email requirement, which is already in the schema. Since schema coverage is high, the baseline is 3, and the description does not significantly augment the schema's information.

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 sends a tour brochure (PDF) to a specified email address using the precise verb 'sends' and resource 'tour brochure (PDF file)'. The leading phrase 'Use this when the user requests a tour brochure or PDF to be sent to their email' precisely identifies the trigger, distinguishing it from sibling tools like tourradar_web-tour-booking or tourradar_web-ask-question.

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: 'Use this when the user requests a tour brochure or PDF to be sent to their email.' It also provides clear prerequisites and handling instructions: ensure the user has provided their email, ask if not, and never generate or assume email addresses. However, it does not mention when not to use it or name alternative tools, so it misses the 'when-not' component of a top score.

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. It discloses that the tool routes automatically and returns a combined answer, but it does not mention potential side effects, whether it only performs read-only actions, or any limitations (e.g., not booking directly). This is adequate but not rich.

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 plus an example convey the entire purpose and usage. No redundant text, efficient and 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 tool with one parameter and an output schema, this description is largely complete. It gives the behavioral model, an example, and implies coverage across multiple travel domains. Missing details about error handling or latency are minor for an agent tool.

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 0%, so the description must compensate. It clarifies that 'query' should be a natural-language travel question and provides a concrete example ('Cheapest flights from Zurich to Rome next week, and do I need a visa?'), adding meaning beyond the bare parameter name.

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 it is a natural-language travel agent that routes to the right tools and returns a combined answer. This distinguishes it from the many specialized sibling tools (e.g., skiplagged_sk_flights_search, visa_check) by framing it as an orchestrator.

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 tells users to ask a travel question in natural language, implying this tool is the entry point when you don't know which specific tool to call. It doesn't explicitly state when not to use it or name alternatives, but the routing behavior and example effectively convey the intended usage.

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 for behavioral disclosure. It does not mention that this is a read-only search, what the response looks like, any rate limits, or the radius-based nature of the search (despite the tool name). It only describes the action without detailing expected behavior or side effects.

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 exceptionally concise: two sentences covering purpose and usage context, plus a structured 'Additional Information' block with current date details. Every sentence earns its place with no fluff or 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?

The tool is complex with 14 parameters, nested filter objects, and no output schema, yet the description offers no guidance on result format, search behavior, or how the parameters fit together. The minimal text is insufficient for such a complex tool, leaving the agent reliant entirely on the schema without an overarching operational context.

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 adds no extra parameter context beyond 'using coordinates,' which is already covered by the latitude/longitude schema descriptions. It neither compensates nor misleads, so the baseline holds.

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 function: 'Search for accommodations and hotels using coordinates on trivago.' It specifies a concrete verb, a resource type, and the coordinate-based method, which distinguishes it from the sibling tool 'trivago_trivago-accommodation-search'.

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 usage context with 'Use this tool when you want to find accommodations near a specific location (landmark, neighborhood, or address).' However, it does not explicitly mention alternatives or when-not-to-use cases, so it stops short of the highest guidance level.

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 bears the full burden of behavioral disclosure. It only states the high-level action and does not mention whether the operation is read-only, what results look like, or any constraints or side effects. This is a significant gap for a search 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 main sentence is concise and front-loaded. However, the appended 'Additional Information' JSON is largely redundant with the schema's date context and adds noise, preventing a perfect score.

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?

This is a complex tool with 13 parameters, nested objects, no output schema, and no annotations, yet the description is a single high-level sentence. It omits operational details such as required date parameters, date ordering constraints, and filter options, leaving the agent under-informed 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%, and the schema already provides rich descriptions for all parameters. The tool description adds minimal value beyond identifying 'query' as destination or point of interest, 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 uses a specific verb ('Search'), identifies the resource ('accommodations and hotels'), and specifies the scope ('by destination or point of interest on trivago'). This clearly distinguishes it from the sibling radius-search tool and other accommodation search 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 implies use when a user wants to find accommodations by destination or point of interest, but it provides no explicit when-to-use/when-not-to-use guidance or alternatives. There is no exclusion of other search types such as radius-based searches.

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?

Since no annotations are provided, the description is entirely responsible for behavioral disclosure. It only restates the basic function without mentioning any side effects, data sources, rate limits, or response characteristics. This leaves the agent without insight into the tool's operational 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 a single, concise sentence that is front-loaded and free of unnecessary words. It efficiently conveys the core purpose without redundant detail.

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 two-parameter tool, the description provides the minimum viable understanding of the task. However, it lacks usage guidance and parameter clarity, and since there are no annotations to supplement, the overall completeness is average.

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 the parameters. It mentions 'passport country' and 'destination,' which loosely maps to the 'passport' and 'destination' fields, but it does not clarify input formats (e.g., country codes vs. names) or any constraints, leaving significant ambiguity.

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 function: checking visa requirements for a passport country visiting a destination. It uses a specific verb and resource, making the purpose unmistakable, though it does not explicitly distinguish itself from the sibling tool visa_summary.

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?

No guidance is provided on when to use this tool versus alternatives like visa_summary. The description only states what the tool does, with no context on appropriate scenarios or exclusions.

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 output is counts by category, which is valuable. However, it does not mention data coverage, potential limitations, or whether the operation has any side effects (though it is clearly 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?

The description is a single, well-structured sentence that immediately conveys the tool's purpose without unnecessary words. It is appropriately sized and 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?

The tool is simple with one parameter, and an output schema exists, reducing the need for return-value explanation. However, the description leaves gaps: no param format, no usage guidance, and no differentiation from the sibling visa_check tool. It is adequate but 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 has one parameter 'passport' with no description (0% schema coverage). The description adds that it refers to a 'passport country,' which clarifies its meaning, but it does not specify the accepted format (e.g., country name, ISO code) or provide examples. With no schema coverage, the description should compensate more.

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 function: providing an overview of visa-free access for a passport country with counts by category. It uses specific phrasing like 'Overview of visa-free access' and 'counts by category,' which makes the purpose evident. It does not explicitly distinguish from sibling tools like visa_check, but the 'summary' scope implies a different use case.

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?

There is no guidance on when to use this tool versus alternatives. The sibling list includes visa_check, which likely handles specific visa checks, but the description does not mention situational advice, prerequisites, or when to avoid using this tool.

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