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

No annotations are provided, so the description carries full burden. It states this is an additive operation but doesn't disclose behavioral traits like whether it requires payment, affects reservation totals, allows removal of extras, has rate limits, or returns confirmation details. This is inadequate for a mutation tool with zero annotation coverage.

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 with no wasted words. It front-loads the core purpose and includes helpful examples without unnecessary elaboration.

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 annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on mutation effects, error conditions, return values, and parameter usage, making it insufficient for reliable tool invocation in this 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 0%, so the description must compensate. It mentions 'optional extras' and examples, which loosely map to the 'extras' parameter, but doesn't explain 'confirmation_number' or 'last_name' semantics, nor details like extra ID formats or quantity constraints. Baseline is 3 as it adds some value but doesn't fully cover the 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 action ('add') and target ('optional extras to an existing reservation'), with specific examples (GPS, child seats, etc.). It distinguishes from siblings like 'create_reservation' or 'modify_reservation' by focusing on extras, though it doesn't explicitly contrast with them.

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 adding extras to an existing reservation but provides no guidance on when to use this versus alternatives like 'modify_reservation' (which might also handle extras), prerequisites (e.g., reservation must be active), or exclusions (e.g., cannot add after pickup).

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 mentions the free cancellation policy, which is valuable context beyond basic functionality. However, it doesn't address other important behavioral aspects like whether cancellation is reversible, what confirmation is provided, or potential fees outside the 24-hour window, leaving significant 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?

The description is perfectly concise with two sentences that each serve distinct purposes: the first states the core function, the second provides critical usage context. There's no wasted verbiage, and information is front-loaded appropriately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a destructive operation with no annotations and no output schema), the description provides basic purpose and timing context but lacks crucial information about return values, error conditions, authentication needs, and complete parameter documentation. It's minimally adequate but has clear gaps for a cancellation 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 only 33% (only the 'reason' parameter has a description), and the tool description adds no parameter information beyond what's in the schema. For a tool with 3 parameters where 2 are completely undocumented in both schema and description, this is inadequate compensation for the low 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 clearly states the specific action ('Cancel') and target resource ('an existing Hertz reservation'), distinguishing it from siblings like 'modify_reservation' or 'create_reservation'. It provides a precise verb+resource combination that leaves no ambiguity about the tool's function.

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 includes explicit timing guidance ('Free cancellation is available up to 24 hours before pickup'), which helps determine when to use this tool. However, it doesn't specify alternatives (e.g., when to use 'modify_reservation' instead) or mention prerequisites like authentication requirements, which would elevate it to 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 full burden for behavioral disclosure. While it implies a write operation ('Create'), it doesn't specify whether this is a booking confirmation, a draft reservation, what permissions are needed, whether it's idempotent, what happens on failure, or what the response contains. For a mutation tool with 14 parameters, this is insufficient behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. Every word contributes to understanding what the tool does, though it could benefit from additional context about behavioral aspects given the lack of annotations.

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 complex reservation creation tool with 14 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address error conditions, response format, authentication requirements, or how this tool relates to the sibling tools in the system. The agent would need to guess about many important operational aspects.

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 mentions four parameter categories (vehicle selection, location details, dates, driver information) which map to some of the 14 parameters. With schema description coverage at 57%, the description adds some value by grouping parameters semantically, but doesn't fully compensate for the coverage gap or provide format details beyond what the schema already documents for most 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 action ('Create a new Hertz car rental reservation') and specifies the resource type, making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'modify_reservation' or 'get_reservation' beyond the obvious creation vs. modification/retrieval 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?

The description provides no guidance on when to use this tool versus alternatives like 'modify_reservation' or 'cancel_reservation'. It lists required data fields but doesn't indicate prerequisites, dependencies, or appropriate contexts for invocation beyond the basic function.

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 mentions the search functionality and return details, but lacks critical information such as authentication requirements, rate limits, error handling, or pagination behavior. For a search tool with multiple parameters, this is a significant gap in transparency.

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 and front-loaded, consisting of two efficient sentences that directly state the tool's purpose and output. Every sentence earns its place without redundancy, making it easy to 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?

Given the complexity of a search tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication, rate limits, or error handling, and lacks details on the return format beyond high-level categories. This leaves significant gaps for an AI agent to use the tool effectively.

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 minimal value beyond the input schema, which has 100% coverage. It mentions search criteria (city, airport, coordinates) and return details, but doesn't explain parameter interactions or provide additional context like default behaviors beyond the schema's 'radius_miles' description. With high schema coverage, 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 searches for Hertz rental locations near specified criteria and returns location details. It specifies the verb 'search' and resource 'Hertz rental locations' with scope 'near a city, airport, or coordinates.' However, it doesn't explicitly differentiate from sibling tools like 'search_vehicles' or 'get_vehicle_details,' which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning search criteria (city, airport, coordinates) and return details, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_vehicles' or 'get_vehicle_details.' No exclusions or prerequisites are stated, leaving usage context somewhat vague.

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 implies a read-only operation ('Check'), but doesn't explicitly state whether it's safe, requires authentication (beyond the PIN parameter), has rate limits, or what happens on errors. For a tool with authentication parameters and no annotations, this leaves significant behavioral 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?

The description is a single, efficient sentence that front-loads the purpose and key details (tier, points, certificates). There's no wasted language or redundancy, making it easy to parse quickly. Every word contributes directly to understanding the tool's function.

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 (authentication parameters, no output schema), the description is minimally adequate. It covers what data is returned but lacks details on authentication requirements, error handling, or output format. Without annotations or an output schema, the description doesn't fully compensate for these gaps, leaving room for improvement in completeness.

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, with clear documentation for all three parameters (member_id, email, pin). The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or usage tips. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Check') and resource ('Hertz Gold Plus Rewards loyalty status'), listing the exact data returned (tier, points balance, free day certificates). It distinguishes itself from sibling tools like 'get_reservation' or 'get_vehicle_details' by focusing on loyalty program information rather than reservations or vehicles.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing authentication via PIN), scenarios where it's appropriate (e.g., customer service inquiries), or exclusions (e.g., not for modifying loyalty data). With sibling tools like 'get_reservation' available, there's no differentiation in 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?

No annotations are provided, so the description carries full burden. It states 'retrieve' which implies a read operation, but doesn't disclose behavioral traits such as whether it requires authentication, rate limits, error handling, or what the return format looks like (e.g., structured data vs. text). For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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?

Single sentence, front-loaded with the core purpose, efficiently lists key policy aspects without redundancy. Every word earns its place by specifying what policies are included, making it appropriately sized and easy to scan.

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 annotations, no output schema, and 3 parameters with incomplete schema coverage, the description is inadequate. It doesn't explain return values, error cases, or behavioral context needed for a tool that retrieves complex policy data. For a read operation with potential variability based on inputs, more completeness is required to guide effective use.

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 67% (2 out of 3 parameters have descriptions), with location_id and country documented but vehicle_class lacking a description. The description adds no specific parameter semantics beyond what the schema provides—it doesn't explain how location_id affects policies, what vehicle_class enums mean in context, or default behaviors for country. Baseline 3 is appropriate given moderate 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 clearly states the verb 'retrieve' and the resource 'Hertz rental policies', with specific examples of what policies are included (age requirements, fuel policy, etc.). It distinguishes from siblings like get_locations or get_vehicle_details by focusing on policies rather than locations or vehicle specs. However, it doesn't explicitly differentiate from get_reservation which might also involve policy details.

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 explicit guidance on when to use this tool versus alternatives like get_reservation (which might include policy info) or search_vehicles (which could relate to policies). The description implies usage for retrieving policy information, but lacks context on prerequisites, timing, or exclusions (e.g., when location-specific policies are needed).

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. It clearly indicates this is a read operation ('Look up'), which is helpful, but doesn't disclose other behavioral traits like authentication requirements, rate limits, error conditions, or what data is returned. It adds basic context but lacks operational 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?

Single sentence, zero waste. Every word earns its place: verb, resource, and required identifiers are front-loaded. No redundant information 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 lookup tool with 2 parameters and 100% schema coverage, the description is adequate but minimal. No output schema exists, so the description doesn't explain return values (e.g., reservation details). With no annotations, it could benefit from more behavioral context, but it meets basic needs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description mentions the parameters but doesn't add meaningful semantics beyond what's in the schema (e.g., format examples, validation rules). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Look up') and resource ('existing Hertz reservation'), and distinguishes it from siblings like 'create_reservation' or 'modify_reservation' by specifying it's for retrieval only. It precisely identifies the lookup method using confirmation number and last name.

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 (when you have a confirmation number and last name to retrieve a reservation), but doesn't explicitly state when to use this versus alternatives like 'search_vehicles' or 'get_vehicle_details'. No exclusions or prerequisites 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 of behavioral disclosure. It states the tool retrieves 'detailed information and pricing,' but doesn't specify what details are included, whether pricing is dynamic or static, if authentication is required, or any rate limits. For a read operation with zero annotation coverage, this lacks critical behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Get detailed information and pricing'). There is no wasted language or redundancy, making it highly concise and well-structured for quick understanding.

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 complexity of a tool that retrieves vehicle details and pricing, the description is incomplete. With no annotations and no output schema, it fails to explain what information is returned (e.g., specifications, availability, pricing breakdown) or behavioral aspects like error handling. This leaves significant gaps for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters ('vehicle_id' and 'rate_code') well-documented in the schema. The description adds minimal value beyond the schema by implying 'vehicle_id' comes from search results and 'rate_code' affects pricing, but doesn't provide additional syntax or format details. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'detailed information and pricing for a specific vehicle from search results.' It distinguishes this tool from siblings like 'search_vehicles' (which likely returns multiple vehicles) and 'get_reservation' (which focuses on reservations rather than vehicle details). However, it doesn't explicitly contrast with all siblings, 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. It doesn't mention prerequisites (e.g., that 'vehicle_id' must come from search results), when not to use it, or how it differs from similar tools like 'get_reservation' or 'search_vehicles.' This leaves the agent to infer usage context, which is inadequate.

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 states the tool modifies a reservation but doesn't cover critical aspects like whether changes are reversible, if it requires authentication, potential rate limits, error conditions (e.g., invalid confirmation number), or what the response includes. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core purpose ('Modify an existing Hertz reservation') and lists key modifiable elements. There is no wasted text, and it's appropriately sized for the tool's complexity.

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 complexity of a 7-parameter mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter meanings beyond basic hints, and expected outcomes. For a tool that modifies reservations—a potentially sensitive operation—more context is needed to ensure safe and correct usage.

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 low at 29%, with only 2 out of 7 parameters having descriptions in the schema. The description mentions 'change dates, locations, or vehicle class', which hints at parameters like new_pickup_datetime and new_vehicle_class, but doesn't explain semantics for confirmation_number, last_name, or the distinction between pickup/dropoff parameters. It adds minimal value beyond the schema, failing to compensate for the coverage 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 ('modify') and resource ('existing Hertz reservation'), and specifies what can be changed ('dates, locations, or vehicle class'). It distinguishes from siblings like 'cancel_reservation' and 'create_reservation' by focusing on updates rather than creation or cancellation. However, it doesn't explicitly differentiate from 'get_reservation' or other tools beyond the modification aspect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid reservation), exclusions (e.g., cannot modify after pickup), or comparisons to siblings like 'cancel_reservation' or 'create_reservation'. Usage is implied by the name but not explicitly stated.

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

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 adds value by specifying that it 'Returns a list of available cars with pricing,' which clarifies the output format. However, it lacks details on rate limits, authentication needs, or potential errors, leaving gaps in behavioral context for a search tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence and adds output information in the second. Both sentences earn their place by clarifying the tool's function and return value, with zero waste or redundancy, making it appropriately sized and 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 complexity of 9 parameters, no annotations, and no output schema, the description is moderately complete. It covers the purpose and output format but lacks details on behavioral traits like error handling or usage constraints. For a search tool with rich parameter schema but no other structured data, it should do more to compensate for missing annotations and 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%, so the schema already documents all 9 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'dates, locations, and preferences,' which aligns with parameters like pickup/dropoff and vehicle_class. Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't provide additional syntax or format insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Search for available vehicles'), the resource ('at Hertz'), and the scope ('for specific dates, locations, and preferences'). It distinguishes this tool from siblings like 'get_vehicle_details' or 'create_reservation' by focusing on availability search rather than reservation management or detailed vehicle information.

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 through 'Search for available vehicles... for specific dates, locations, and preferences,' suggesting when to use this tool. However, it doesn't explicitly state when not to use it or name alternatives among siblings, such as 'get_vehicle_details' for non-availability information or 'get_locations' for location data without vehicle search.

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