Bela Vista

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

Since no annotations are provided, the description must disclose all behavioral traits. It does so comprehensively: returns a checkout URL, the booking stays off the venue's calendar until payment, slot re-validation happens, and the contact email is not verified at this step. This fully informs the agent about the tool's 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 detailed but each sentence serves a purpose. It is front-loaded with the most critical information (nothing booked until payment) and then provides procedural steps. While slightly verbose, it remains efficient 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 complexity (6 params, nested objects, no output schema), the description covers all necessary aspects: preconditions (call get_availability), what it returns (checkout URL), side effects (nothing booked), and post-conditions (user must pay). It is complete for the agent to use correctly.

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

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

Schema description coverage is 100%, so the description adds important context beyond the schema: it clarifies that start/end dates must be exactly as returned by 'get_availability', that contact email is not verified, and that resourceId is optional for a specific professional. This adds significant 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 specifies that the tool books an appointment slot at a venue via Wix Bookings. It uses explicit action words ('book an appointment slot') and distinguishes itself from sibling tools like 'reserve_event_tickets' or 'request_reservation' by focusing on booking appointments, not events or dining.

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: call 'get_availability' immediately before this tool, explains that the slot is re-validated server-side, and warns that nothing is booked until payment via the returned checkout URL. It also tells the user to open the link, covering when and how to use the 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?

With no annotations, description conveys key behavior: creates a URL, user completes payment, no login needed. Does not detail return format or potential errors, but covers main safety and interaction aspects.

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, no fluff. The core purpose and key usage detail (no login) are front-loaded. Every word 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?

Adequate for a simple tool with one parameter, but missing return format and error conditions. With no output schema, the description should ideally state what the tool returns (e.g., a URL).

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?

Input schema has 100% coverage with clear descriptions for each parameter (items, productId, quantity). Description adds no extra nuance beyond the schema, so 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?

Description clearly states the verb 'create', the resource 'direct checkout URL', and the scope 'for one or more store products (Wix Stores)'. It distinguishes from sibling tools like list_products or create_booking by focusing on payment URL generation.

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?

Implied usage: use when needing a checkout URL for products. Notes that no AI agent login is required, but lacks explicit when-to-use vs. alternatives or exclusion criteria.

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 exist, so the description carries full burden. It discloses a key behavioral trait: 'slot times are returned in the VENUE's timezone, which is not necessarily the directory's.' This adds value beyond the schema. It implies read-only behavior (no destructive hints needed).

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 purpose, every word earns its place. 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?

Without an output schema, the description does not explain the return structure (e.g., what each time slot contains). It mentions time slots and timezone but lacks detail on format (start/end, capacity). Given the tool's simplicity, it is adequate but could be more complete.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context: serviceId comes from list_booking_services, date format is reinforced, and place_slug should match that used in the sister tool. This adds meaning beyond the schema 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 clearly states 'Get available time slots for a bookable service on a given date (Wix Bookings).' It uses a specific verb (Get) and resource (time slots) and distinguishes from siblings like list_booking_services (lists services, not slots) and create_booking (creates bookings).

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: pass serviceId from list_booking_services, date in YYYY-MM-DD, and use the same place_slug. It also clarifies timezone behavior. It implies when to use (to get available slots before booking) but does not explicitly state when not to use.

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 discloses the return values (ticket names, prices, sale status, quantity left) and implies a read-only operation. This is transparent and sufficient for the tool's simple nature.

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 purpose, followed by a concise usage hint. Every word earns its place; no unnecessary 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 simple with one parameter and no output schema. The description adequately covers its functionality and expected output, making it complete for an AI agent to use correctly.

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

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

The schema has 100% coverage for the single parameter, and the description adds value by explaining the context ('Pass the event slug from list_events') and what the parameter represents. This goes beyond the schema description.

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

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

The description clearly states the tool gets ticket types and prices for a specific event, specifying the input (event slug) and the output (names, prices, sale status, how many left). It is specific and actionable, though it doesn't explicitly differentiate from sibling tools like reserve_event_tickets or rsvp_event.

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 advises to 'Pass the event slug from list_events,' which implies a prior step, but provides no explicit guidance on when not to use this tool or what alternatives exist. The usage context is implied but not fully delineated.

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 operation is read-only and lists the return content. However, it does not mention authentication requirements or potential errors (e.g., if loyalty program is not available).

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 'Get the loyalty/rewards program details'. It is concise with no wasted words, earning 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 zero-parameter, no-output-schema tool, the description is reasonably complete. It specifies the returned fields. However, it could mention error handling or conditions (e.g., program existance).

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 schema description coverage is 100%. The description adds no param-level info, as none exist. Baseline of 4 is appropriate since schema already tells all there is to know.

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 retrieves loyalty/rewards program details, naming specific return fields (program name, points currency, tier structure). This distinguishes it from other get_ tools like get_site_info which serves a different 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 no guidance on when to use this tool versus alternatives. There are no exclusions or context such as 'only if loyalty program is active' or 'use get_site_info for general site info'. The implicit hint 'for this site' is insufficient.

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 explicitly lists the returned data fields (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood), making the tool's behavior clear as a read operation. It does not note permissions or rate limits, but the 'get' name implies safety.

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 core action ('Get full details...'), and efficiently enumerates return fields. While compact, it packs all necessary information without 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?

Given no output schema and low complexity (one parameter, no nesting), the description sufficiently covers return values. It lists key fields but omits error conditions or expected size. Still, it is fairly complete for the tool's simple nature.

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% (slug parameter described). The description adds minimal value beyond the schema—it mentions 'by its URL slug' but does not elaborate on format or constraints beyond the schema's example. 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 'Get full details for a specific place by its URL slug', which is a specific verb+resource. It distinguishes from sibling tools like 'search_places' (search) and 'list_categories' (list) by emphasizing the use of a URL slug for a single place.

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 a specific place's URL slug, but it does not explicitly mention when to use this tool versus alternatives like 'search_places' or when not to use it. No exclusion criteria or alternative suggestions 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?

No annotations provided, so description carries full burden. It lists return fields but lacks details on error conditions, authentication, rate limits, or side effects. For a read-only menu tool, 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?

Two sentences front-loaded with purpose and output details, followed by prerequisite guidance. No unnecessary 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 simple parameter and no output schema, the description comprehensively covers what the tool does and what it returns, leaving no major gaps for its complexity level.

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 covers place_slug with 100% description coverage. The description reinforces the parameter's origin (from search_places or list_categories), adding practical context beyond the schema's example.

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 the food menu), the resource (a specific restaurant), and the data returned (sections, dishes, descriptions, prices, dietary labels). It distinguishes from siblings like search_dishes by scoping to one restaurant.

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 instructs to use search_places or list_categories first to obtain the required place_slug, providing clear when-to-use guidance and alternative tools for prerequisite steps.

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. The description does not disclose whether this is a read-only operation (though implied by 'get'), any authentication needs, rate limits, or pagination behavior beyond the limit parameter. The behavioral context is minimal and relies on inference.

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 efficiently conveys the tool's purpose and output. No extraneous words or repetition. It is front-loaded with the verb and resource.

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 only one parameter, the description is borderline adequate. It explains what the tool does and what it returns, but it lacks detail on ordering, filtering (e.g., by date or rating), and any usage caveats. It meets the minimum for a simple read tool but leaves room for improvement.

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

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

The schema has 100% description coverage for its single parameter (limit). The description adds value by listing the output fields (reviewer name, rating, title, content), which are not in the input schema. This helps the agent understand what data will be returned, going beyond the schema 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 the action ('Get') and resource ('published reviews for this site (Wix Reviews)'). It also specifies the return fields (reviewer name, rating, title, content), distinguishing it from sibling tools that deal with other entities like bookings, events, or products.

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 vs. alternatives (e.g., list_products, list_blog_posts). There is no mention of prerequisites, filtering options, or when not to use this tool. The description is purely functional.

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 return structure (cinema, session times, format, language) and a prerequisite, but lacks details on rate limits, data freshness, or handling of cases with no showtimes. Adequate but not thorough.

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 with a separate prerequisite note. It is front-loaded with the purpose and contains no redundant information, earning 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?

Despite lacking an output schema, the description explains the return structure (cinema, session times, format, language) and includes the prerequisite. For a retrieval tool, this is sufficiently complete, though more detail on error handling could improve it.

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%, and the description adds context beyond the schema: it mentions that movie_slug comes from list_movies and date defaults to today (BRT). This helps an agent understand parameter origins and defaults.

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 'Get showtimes for a specific movie at cinemas in this neighborhood, for a given date', specifying the verb, resource, and scope. It distinguishes itself from siblings like list_movies (which lists movies) and get_event_tickets (events).

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 mentions a prerequisite ('Requires movies_enabled on this site') but does not explicitly state when to use this tool versus alternatives. The context of siblings provides implicit guidance, but no explicit when-not-to-use or alternative naming is present.

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 describes the return values but does not disclose if the data is real-time or cached, or any potential side effects. For a read-only info tool, this is adequate but could be more 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 two sentences with no wasted words. It front-loads the main functionality in the first sentence and provides a specific use case in the second. Each sentence is valuable.

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 lists the major categories of returned information (basic info, time, weather). It is complete for a simple info tool, though it could be more detailed about the structure of the weather data.

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?

There are no parameters, so the input schema is trivially covered. The description adds meaning by detailing what information is returned, compensating for the lack of param documentation. Baseline for 0 params is 4.

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 basic information about the neighborhood directory, including specific data like local time and weather. It uses a specific verb-resource pair and differentiates itself from sibling tools by highlighting the unique time/weather feature.

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 for any what time is it there or what's the weather like context,' providing clear context for when to use. It does not include exclusions or alternatives, but the guidance is sufficient given the sibling tools list.

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 responsibility. It does not disclose that the operation is read-only, nor does it mention ordering (implied 'recent' but not explicit), pagination, error conditions, 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 a single sentence that efficiently conveys the tool's purpose and return fields. It is nearly optimally concise with minimal 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 list tool with two optional parameters and no output schema, the description covers the primary purpose and return fields. It could mention ordering or pagination, but is otherwise complete.

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

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

Schema coverage is 100%, and both parameters (limit, category) are already described in the schema. The description adds no additional meaning beyond confirming the filter context. 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 action ('list'), the resource ('recent published blog posts'), and the context ('Wix Blog'), and enumerates the return fields. It is distinct from sibling tools like list_events or list_products.

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 does not provide guidance on when to use this tool versus alternatives, such as list_categories or list_events, nor does it specify 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 fully discloses behavioral traits: it lists all services regardless of bookability, indicates bookableViaMcp flag, notes id is null when not bookable, and explains the effect of omitting place_slug. It also clarifies that services are listed even for venues without online booking.

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

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

The description is front-loaded with the core purpose and provides necessary details in a logical order. It is slightly long but every sentence adds value; could be marginally more concise, but still 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?

Despite no output schema, the description thoroughly explains return fields (name, description, price, duration, bookableViaMcp, id) and handles edge cases (bookableViaMcp false, place_slug omitted). It gives the agent everything needed to use the tool correctly in 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?

Although the schema already covers the parameter with a description, the tool description adds significant nuance: the effect of omitting place_slug, the distinction between venue and directory services, and the integration with create_booking. This adds value beyond the schema, but since schema coverage is 100%, a score of 4 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 lists a venue's services with price and duration, and distinguishes between using place_slug (venue-specific) and omitting it (directory's own services). It specifies the verb 'list' and the resource 'venue services', 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?

The description provides explicit guidance: pass place_slug from search_places for venue services, which is the typical use case; omitting it gives directory's services (rarely used). It also explains what to do when bookableViaMcp is false—direct user to bookingUrl or venue page—and notes that serviceId works with create_booking.

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 provided, so description carries full burden. It states the tool returns data but does not explicitly confirm it's a read-only operation or mention any constraints (e.g., caching, rate limits). However, the absence of parameters and the 'Returns' phrasing imply idempotency.

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 that is front-loaded with the main action and efficiently enumerates output components. No extraneous text.

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, description fully explains the return value (top-level groups, subcategories, localized labels, schema.org types, place counts). No ambiguity for a zero-parameter list 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?

No parameters in schema, so description adds meaning by detailing what the response contains. Schema coverage is 100% (empty), and description compensates fully by specifying the output structure.

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?

Clear verb 'Returns' and specific resource 'category taxonomy' with detailed components (groups, subcategories, localized labels, schema.org types, place counts). Distinguishes from sibling list_ tools by focusing on taxonomy structure.

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 when/when-not guidance, but purpose is clear and tool is straightforward with no parameters. Implicitly, use when you need the full category hierarchy. No reliance on context 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, the description carries full burden. It discloses behavioral traits such as weatherForecast for nearby events and the live resolution of the 'agora' filter. However, it does not explicitly state read-only nature 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 concise and front-loaded with the main purpose. It uses a single paragraph that efficiently conveys key functionality without verbosity.

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 list tool with 3 parameters and no output schema, the description covers the primary use case, special features, and filter behavior. It lacks explicit mention of output format but is otherwise 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 coverage is 100%, so the description adds marginal value. It elaborates on the 'agora' filter behavior, but overall parameter meaning is already clear from 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: listing upcoming events with specific fields (date, venue, price, URL) in a neighborhood. It also highlights a unique feature (weatherForecast for events within 7 days), making it distinct from sibling list tools.

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

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

The description implies when to use the tool (for events in a neighborhood) and explains how to use the filter parameter, but it does not explicitly differentiate from sibling tools or provide guidance on when not to use it.

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 exist, so description carries full burden. It discloses that the tool returns all FAQs grouped by category, which is the expected behavior. No side effects or destructive actions are implied, and the read-only nature is evident from 'Get all FAQ'. Could be improved by mentioning pagination or data freshness, but 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?

Extremely concise: two sentences that front-load the primary purpose and provide immediate usage context. Every word adds value.

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

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

For a simple parameterless tool with no output schema, the description is fully complete. It explains what data is returned (FAQs, grouped by category) and when to use it. No 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?

The tool has zero parameters and schema coverage is 100%. The description does not need to add parameter details. The baseline for no parameters is 4, and the description's mention of categories adds useful 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?

Clearly states the tool retrieves all FAQ questions and answers grouped by category, and specifies its use for answering common site questions like opening hours, parking, policies, etc. This distinguishes it from sibling tools like get_site_info or list_blog_posts.

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

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

Provides explicit guidance on when to use this tool: 'Use this to answer common questions about the site'. It does not explicitly mention when not to use it or name alternatives, but the context is clear enough for an AI agent.

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 burden. It states the tool returns form details (name, ID, field definitions). While it implies a read-only operation, it does not explicitly say it is non-destructive or discuss any side effects, permissions, or rate limits.

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 with no extraneous text. It efficiently conveys the purpose, output, and usage 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 no parameters and no output schema, the description covers what it returns and its purpose. It could mention if all forms are returned or any sorting/filtering, but it is sufficiently complete for a simple listing 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?

The input schema has no parameters (0), so the description naturally adds no parameter details. With 100% schema coverage and no params, a baseline of 4 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 lists contact/signup forms (Wix Forms) and returns form name, ID, and field definitions. It specifies the resource (forms) and action (list), and distinguishes it from sibling tools like list_blog_posts or list_products.

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 before submit_form to discover which fields to fill.' This provides clear when-to-use guidance, though it does not mention when not to use or alternatives beyond submit_form.

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 provided, so description carries full burden. Only states action and nature (curated, ranked) but omits behavioral details like read-only, ordering, pagination beyond limit, or any side effects. Minimal disclosure.

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 concise sentences that front-load the action and purpose. Every word earns its place; 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 no output schema, the description hints at content ('ranked places with editorial notes') but does not specify return fields or structure. Adequate for a simple tool but leaves gaps about what each guide entry contains.

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 has 1 parameter (limit) with full description. The tool description does not add any additional meaning to the parameter or explain its usage, so it meets baseline but adds no 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?

Clearly states verb 'List', resource 'curated editorial guides', and provides context of being ranked with editorial notes. Distinguishes from siblings like list_blog_posts by emphasizing curated nature and use for 'best of' questions.

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

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

Provides explicit use case: 'The best source for "best X in this neighborhood" questions.' Lacks explicit when-not-to-use or alternatives, but the context is clear.

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 fully bears the burden. It discloses that the tool is a read operation, returns multiple categories of movies, and includes specific fields. It does not mention rate limits or authentication, but for a list tool, these details are 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 a single paragraph of three sentences, front-loaded with the core purpose and condition, then details on categories and returned fields. 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?

Without an output schema, the description lists key returned fields (title, genres, TMDB rating, runtime, detail URL) and explains the status filter. It does not address pagination beyond the limit parameter or default ordering, but overall it provides sufficient context for an AI to use the tool 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% with both parameters described. The description adds value by explaining the meaning of the 'status' enum values (e.g., 'now_showing' = films with upcoming showtimes) and mentioning that 'limit' controls max return count, reinforcing the schema's explanations.

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 the tool lists movies available in the neighborhood, specifying three categories (now-showing, coming-soon, streaming) and the fields returned (title, genres, TMDB rating, runtime, detail URL). This clearly distinguishes it from sibling tools like list_events or list_products, as it is movie-specific.

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 a precondition ('only on sites with movies_enabled') and implies usage for retrieving movie listings. While it does not explicitly state when not to use the tool or list alternatives, the context and name make it clear that this is for movies, not other entities.

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 notes that FLASH offers have a countdown deadline, which adds behavioral context. However, it does not disclose whether the tool is read-only, requires authentication, has rate limits, or handles pagination. The return fields are described, but not the overall 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 two sentences, front-loaded with the core purpose. Every sentence adds information without redundancy. It is appropriately sized and structured for quick comprehension.

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, the description names the key fields returned (discount label, promo code, CTA link, validity window, business/place), which provides adequate context for an agent. It could mention the response format (e.g., array) or default ordering, but the current level is sufficient for a list tool with simple parameters.

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 both parameters described in the schema. The description adds extra meaning for the 'kind' parameter by noting that FLASH offers have a countdown deadline, but the 'limit' parameter is not elaborated beyond the schema. The added value is marginal, 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 clearly states the verb 'list', the resource 'active promotions and deals', and the scope 'in this neighborhood directory'. It lists specific return fields (discount label, promo code, CTA link, validity window, business). This distinguishes it from sibling tools like list_events or list_products.

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 retrieving active offers via the resource type and filter options, but it does not explicitly state when to use this tool versus alternatives (e.g., list_events) or provide exclusions. The context is clear but lacks direct guidelines.

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 provided, so the description bears full responsibility. It discloses return fields (name, description, price, billing cycle, perks, checkout URL) and the behavioral difference with/without place_slug. While it doesn't mention pagination or error scenarios, for a simple listing tool this is sufficient.

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

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

Three sentences: first states purpose, second gives primary use case with reference, third covers alternative and return info. No filler, front-loaded with key guidance.

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

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

For a single-parameter tool with no output schema, the description covers all necessary aspects: purpose, parameter usage hints, return value summary. It is fully complete for its complexity level.

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 parameter description that already explains the parameter. The description adds value by explaining the two usage contexts (with and without place_slug) and the typical case, going beyond the schema's literal 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?

Clear verb 'List' and resource 'membership or subscription plans'. The description distinguishes between listing venue-specific plans (using place_slug) and directory site plans, making the scope explicit. No sibling tool duplicates this functionality, so differentiation is inherent.

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?

Explicit guidance: 'Pass place_slug to list the plans of a specific VENUE... that is what you want in almost every case.' Also advises against omitting place_slug unless the site has its own plans. This clearly tells the agent when and how to use the 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?

With no annotations provided, the description carries full behavioral burden. It discloses that the tool lists products and returns specific fields, which is useful. However, it does not mention authorization requirements, side effects, or whether the store must exist, leaving some gaps for a tool with no annotation safety net.

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 efficiently conveys the tool's purpose and output. Every word serves a purpose, with no extraneous 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 (2 optional params, no output schema), the description adequately covers what the tool does and what it returns. The mention of 'Wix Stores' provides useful context. It could optionally mention pagination or sorting, but it is complete enough for most use cases.

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 both parameters (q, limit) already described clearly in the input schema. The description adds no additional parameter semantics beyond what the schema provides, so 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 it lists products in the site's store (Wix Stores) and specifies the returned fields (name, price, stock status, product type). The verb 'List' and resource 'products' are specific, and the mention of 'Wix Stores' distinguishes it from other listing tools for different resource types.

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 does not provide explicit guidance on when to use this tool vs alternatives like list_blog_posts or list_categories. However, the tool name and the 'Wix Stores' context imply it is for store products, making usage clear but not explicitly 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 provided, so description must disclose behavioral traits. It specifies what is returned (name, URL, category, metadata) and implies read-only behavior via 'List'. However, it does not mention pagination, rate limits, or authentication needs.

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 with no redundancy. The first sentence defines the purpose with examples, and the second lists return fields. Efficient 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 listing tool with one parameter and no output schema, the description provides sufficient context: what is listed, examples, and return fields. Could mention default limit or sorting but not 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 coverage is 100% with the limit parameter documented. The description adds no additional meaning for the parameter but clarifies the type of profiles being listed, which is not 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 lists solo service-provider profiles, defines them as businesses without fixed location, and gives examples (dog walkers, tutors, personal trainers). This distinguishes it from sibling list tools like list_products or list_categories.

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 does not explicitly state when to use this tool vs alternatives. It implicitly defines the content scope but lacks guidance on context, prerequisites, or when not to use.

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 provided, so description carries full burden. Discloses that restaurant is not notified until confirmation link is clicked, email is sent, link expires, and confirmation is not returned. Comprehensive behavioral disclosure.

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?

Concise and well-structured: front-loaded with purpose, then key behavioral notes. Every sentence adds value, 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?

No output schema, but description adequately explains the outcome (email sent, restaurant not notified) and what the agent should tell the user. Minor gap: does not explicitly state the function's return value (e.g., success status), but the flow is clear enough.

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 does not add significant extra meaning beyond what the schema already provides for each 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 requests a table at a restaurant and explains the asynchronous confirmation flow. It distinguishes itself from the sibling 'create_booking' by emphasizing this is a request, not a confirmed 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?

Provides explicit guidance: use a real email belonging to the person, tell user to check inbox, link expires in 24 hours. Explicitly contrasts with a confirmed booking, helping the agent choose between this and alternatives.

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?

Comprehensively describes behavioral traits: hold is temporary, no payment, expires if not completed, max 10 tickets and 10 ticket types. Since no annotations are provided, the description fully covers safety and 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?

Two sentences, each earning its place. First sentence states purpose and output; second sentence adds critical behavioral details. Front-loaded with the main action.

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, the description adequately explains the return value (checkout URL) and constraints. Missing error handling or auth info, but for a hold tool with good schema coverage, it's reasonably complete.

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

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

Schema already has 100% coverage with descriptions, but the tool description adds extra constraints (max 10 tickets and ticket types) that are not in the schema, enriching the agent's understanding beyond what structured fields provide.

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?

Clearly states the verb 'hold' and resource 'tickets' for events on this Wix site, and specifies the output (checkout URL). It distinguishes from sibling tools by noting that for external events, the ticketUrl should be used instead.

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 (for site-sold events) and when not to (for external events), providing an alternative action (use ticketUrl). Also implies temporary nature, guiding appropriate 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?

No annotations, so description carries full burden. Discloses critical behavioral traits: RSVP is not immediate, confirmation email sent, link expires in 24h, link not returned to caller.

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

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

Three sentences with zero waste. Purpose first, then process, then instruction. Efficient 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?

No output schema, but description explains what the tool does and what to tell the user. Could mention that no return value is expected, but sufficient for an agent to use 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%. Description adds value by emphasizing 'email' must be guest's own, confirmation sent there, and 'event_slug' from list_events. Goes beyond schema 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?

Clearly states 'RSVP to a free event on this site (Wix Events)' using specific verb+resource. Implicitly distinguishes from 'reserve_event_tickets' sibling by noting the event is free.

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 context: nobody on guest list, confirmation email, check inbox, use real address. Does not explicitly mention when not to use, but context implies this is for free events.

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 discloses the search scope (every menu item, all restaurants), grouping behavior, and return fields (price, description, dietary labels, place URL). It also covers the optional query behavior. No annotations are provided, but the description is sufficiently transparent for a read-only 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 description is concise (4 sentences) and front-loaded with the main purpose. Every sentence provides essential information without redundancy. Example usage is 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?

For a simple search tool with two optional parameters and no output schema, the description covers all necessary aspects: inputs, behavior, and output structure (price, description, labels, URL). It is complete for an AI agent to use 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?

Both parameters have schema descriptions (100% coverage). The description adds value by providing a concrete example ('feijoada') and explaining behavior when query is omitted ('list the most-served dishes'). This goes beyond the schema's basic 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 clearly states it finds which restaurants serve a dish, searches every menu item across all restaurants, and groups by dish. It distinguishes itself from sibling tools like 'get_restaurant_menus' by focusing on dish search across all restaurants. The example with 'feijoada' reinforces the 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?

It explicitly says 'Use this for any "where can I eat X" question.' It also explains that omitting the query lists top dishes. It does not explicitly mention when not to use it or compare to alternatives, but the context is clear enough for an AI agent.

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 provided, so description carries full burden. It discloses accent-insensitive and typo-tolerant matching, relevance ranking, precomputed open_now, delivery links, hours format, and common amenity slugs. Thorough disclosure.

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 paragraph of 5 sentences, front-loaded with purpose. Efficient but could benefit from bullet points for readability. Generally 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?

Despite no output schema, the description explains return fields (open_now boolean, attributes array, delivery array, rating, hours). Covers all 6 parameters and common amenity slugs. Complete for a search 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 has 100% description coverage, but the description adds meaning beyond schema: 'accent-insensitive and typo-tolerant' for q, 'ALL must match' for attributes, 'open at this exact moment' for open_now, and result structure details. Exceeds baseline 3.

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 'Search for places' with specific examples (restaurants, cafes, shops) and context 'in this neighborhood'. It clearly distinguishes from siblings like get_place (single place) and search_dishes (dishes only).

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 explains how to compose filters but does not explicitly state when to use this tool versus alternatives like get_place or search_dishes. Usage is implied but lacks direct comparison 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?

Without annotations, the description carries full burden. It only states that the tool submits a form and returns a submissionId. No information is given about side effects, permissions, idempotency, or error conditions, leaving behavioral traits insufficiently disclosed.

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: two sentences with no unnecessary words. The purpose is front-loaded, and the workflow step is clearly stated. 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?

Given the tool's simplicity (2 parameters, no output schema), the description adequately covers the main workflow: prerequisite call to list_forms and return value (submissionId). It lacks details on error handling or fallbacks, but overall it is complete enough for expected 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 100%, so the baseline is 3. The description adds context by referencing list_forms for obtaining the formId and field keys, but does not significantly augment the schema's own descriptions. It reinforces the relationship between parameters without adding new semantic detail.

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: 'Submit a form on behalf of the user (Wix Forms).' It uses a specific verb-resource combination and distinguishes from sibling tools like list_forms, create_booking, etc., by focusing on form submission.

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 usage guidance: 'Call list_forms first to get the formId and field keys.' This establishes a prerequisite and clarifies the tool's context. It does not explicitly state when not to use it, but the guidance is clear enough for proper selection.

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