qasper

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

The description adds valuable behavioral context beyond annotations: it explains what gets created (booking record, calendar entry) and what is returned (confirmation with reference number). While annotations already indicate destructiveHint=true and idempotentHint=false, the description provides concrete implementation details without contradicting 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?

Three tightly focused sentences with zero waste: first states the core action, second explains what it creates/returns, third provides critical usage constraint. Every sentence earns its place and is front-loaded with essential 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 destructive mutation tool with no output schema, the description provides good context about what happens (creates records, adds to calendar) and what's returned (confirmation with reference). It could be more complete by mentioning potential error conditions or side effects, but covers the essential behavioral aspects well.

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?

With 100% schema description coverage, the schema already fully documents all 7 parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline expectation without adding extra value.

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

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

The description clearly states the tool's purpose with specific verbs ('book', 'creates', 'adds') and resources ('appointment', 'booking record', 'business calendar'), and distinguishes it from siblings by specifying it's for booking appointments rather than checking availability, getting info, or other functions.

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 when to use this tool ('ONLY call this if the business has 'booking' in its enabledFeatures array'), providing clear prerequisites and distinguishing it from alternatives like check_availability or send_inquiry for non-booking scenarios.

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?

The annotations already indicate readOnlyHint=true and openWorldHint=true, but the description adds valuable context beyond this by specifying the prerequisite condition (business must have 'booking' in enabledFeatures) and clarifying the return value ('Returns time windows when the business is free'), which helps the agent understand the tool's behavior more fully.

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 efficiently structured with two sentences that each serve a clear purpose: the first explains what the tool does, and the second provides critical usage guidelines. There is no wasted language, and key information is front-loaded.

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

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

Given the tool's moderate complexity, rich annotations, and 100% schema coverage, the description is mostly complete. It covers purpose, usage conditions, and behavioral context well. The main gap is the lack of an output schema, but the description partially compensates by stating what is returned ('time windows when the business is free').

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?

With 100% schema description coverage, the input schema already documents all three parameters thoroughly. The description adds minimal semantic context by mentioning 'specific service' and 'given date', but doesn't provide additional details beyond what's in the schema, meeting the baseline for high 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 tool's purpose with specific verbs ('Check available appointment slots') and resources ('for a specific service at a local business on a given date'), and distinguishes it from sibling tools by specifying it returns time windows when the business is free, unlike get_business_info which provides contact info.

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 guidance on when to use this tool ('ONLY call this if the business has 'booking' in its enabledFeatures array') and when not to use it ('If the business doesn't support booking, share their contact info from get_business_info instead'), clearly naming the 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?

Annotations already declare readOnlyHint=true (safe read) and openWorldHint=true (broad applicability). The description adds valuable context beyond this: it specifies the scope ('local service business'), confirms universal availability ('Always available for any business'), and lists the exact information returned. This enhances understanding without contradicting 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, well-structured sentence that efficiently lists all key information: the action, the data fields, the business type, and availability. Every part earns its place 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?

Given the tool's low complexity (1 parameter, no output schema) and rich annotations (readOnlyHint, openWorldHint), the description is mostly complete. It covers purpose, data fields, and availability. However, it lacks details on output format or error handling, which could be useful since there's no output schema, leaving a minor 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 100% description coverage, with the 'slug' parameter fully documented. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., no extra examples or constraints). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to.

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 ('Get business information') and enumerates the exact data fields returned (name, type, service area, contact details, working hours, supported languages, enabled features). It distinguishes this from siblings like get_services (which would list services offered) or search_businesses (which would find multiple businesses).

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

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

The description provides clear context for when to use this tool ('for a local service business') and states 'Always available for any business,' which implies no restrictions. However, it doesn't explicitly mention when NOT to use it or name specific alternatives like get_services or search_businesses for different needs.

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

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

The description adds behavioral context beyond annotations: it mentions that the tool 'Takes into account emergency requests, weekend rates, and other pricing rules' and 'Always available for any business.' Annotations provide readOnlyHint=true and openWorldHint=true, which align with the description's safe, query-like nature and broad availability, but the description enriches this with specific pricing factors and availability assurance, earning a good score.

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, with two sentences that efficiently convey purpose and key behavioral traits. Every sentence adds value: the first states the core function, and the second explains pricing factors and availability. Minor room for improvement in flow prevents 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?

Given the tool's moderate complexity (4 parameters, no output schema), the description is fairly complete. It covers purpose, behavioral aspects, and availability, but lacks details on return values (e.g., quote format) or error handling. With annotations providing safety and scope hints, it is adequate 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%, so the schema fully documents all parameters. The description adds marginal value by hinting at how parameters like 'isEmergency' and 'requestedDate' affect pricing (e.g., 'emergency requests, weekend rates'), but does not provide new syntax or format details beyond the schema. 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 tool's purpose: 'Get a price quote for a specific service from a local business.' It specifies the verb ('Get'), resource ('price quote'), and scope ('specific service from a local business'), but does not explicitly differentiate from sibling tools like 'get_business_info' or 'get_services' in terms of pricing focus, 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 context by mentioning factors like emergency requests and weekend rates, but does not explicitly state when to use this tool versus alternatives such as 'get_services' for service lists or 'send_inquiry' for general queries. It lacks clear exclusions or named alternatives, leaving some ambiguity.

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 already declare readOnlyHint=true and openWorldHint=true, indicating safe read operations with open-world data. The description adds valuable context beyond annotations: it specifies the catalog content structure and availability guarantee ('Always available for any business'), which helps the agent understand behavioral traits like reliability and data format.

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 highly concise and front-loaded, consisting of two efficient sentences. The first sentence clearly states the purpose and key details, while the second adds important behavioral context. There is no wasted language, 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 (1 parameter, no output schema) and rich annotations (readOnlyHint, openWorldHint), the description is mostly complete. It covers purpose, content, and availability, but lacks details on output format or error handling, which could be helpful despite annotations. However, for this simple tool, it's 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?

Schema description coverage is 100%, with the single parameter 'slug' fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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 ('Get') and resource ('service catalog for a local service business') with specific content details (service names, descriptions, durations, price ranges). It distinguishes from siblings like 'get_pricing' by covering broader catalog information, but doesn't explicitly contrast with 'get_business_info' which might overlap.

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 ('for a local service business') and states 'Always available for any business,' suggesting universal applicability. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_pricing' or 'get_business_info,' leaving some ambiguity about sibling differentiation.

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?

The description adds valuable behavioral context beyond annotations. Annotations indicate read-only and open-world hints, but the description elaborates on search capabilities ('Supports both text-based location search and precise coordinate-based proximity search') and result details ('Each result includes an 'enabledFeatures' array...'). It doesn't contradict annotations and provides useful operational insights.

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 and concise, with three sentences that each add distinct value: purpose, usage guidelines, and behavioral details. It avoids redundancy and is front-loaded with essential information, making it efficient and easy to parse.

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

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

Given the tool's complexity (6 parameters, no output schema) and rich annotations, the description is largely complete. It covers purpose, usage, and key behavioral traits. However, it doesn't detail output format or pagination, which could be helpful for a search tool. With annotations providing safety context, it's mostly sufficient but has 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?

With 100% schema description coverage, the input schema already documents all 6 parameters thoroughly. The description mentions 'category and/or location' and 'text-based location search and precise coordinate-based proximity search,' which aligns with but doesn't significantly expand upon the schema's parameter descriptions. The baseline score of 3 reflects adequate but not enhanced parameter semantics.

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

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

The description clearly states the tool's purpose: 'Search for available local service businesses by category and/or location.' It specifies the verb ('search'), resource ('local service businesses'), and scope ('by category and/or location'), distinguishing it from sibling tools like 'book_appointment' or 'get_business_info' 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 description explicitly states when to use this tool: 'Use this to find businesses before checking availability or booking.' It provides clear guidance on its role in the workflow and distinguishes it from siblings like 'check_availability' and 'book_appointment' by positioning it as a preliminary step.

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?

The description adds valuable behavioral context beyond annotations: it states that 'The business owner will be notified immediately via SMS and will contact the customer directly,' which clarifies the notification mechanism and follow-up process. Annotations provide hints (e.g., destructiveHint: true), but the description enriches this with real-world implications without contradicting them.

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, followed by usage guidelines and behavioral details in three concise sentences. Each sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 action with five required parameters) and lack of output schema, the description is mostly complete. It covers purpose, usage, and behavioral context well, but could benefit from mentioning potential error cases or response formats, though annotations help mitigate this 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description does not add significant meaning beyond the schema, such as explaining interdependencies or usage nuances for parameters like 'slug' or 'message.' It 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 tool's purpose: 'Send a general inquiry to a local service business.' It specifies the verb ('send') and resource ('inquiry'), and distinguishes it from siblings by noting it's for questions, custom quotes, or issues that don't fit bookable services, unlike tools like 'book_appointment' or 'get_pricing'.

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 guidance on when to use this tool: 'when the customer has a question, needs a custom quote, or wants to describe an issue that doesn't fit a specific bookable service.' It also includes a clear exclusion: 'ONLY call this if the business has 'inquiry' in its enabledFeatures array,' which helps differentiate it from alternatives like 'book_appointment' or 'get_services'.

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