Vila Mariana

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

With no annotations provided, the description fully discloses behavioral traits: the tool returns a checkout URL, does not finalize booking, server-side re-validates the slot, and contact email is unverified. No contradictions.

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, but the dense paragraph style could be improved with bullet points for readability. Nevertheless, every sentence 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?

Covers all necessary behavioral aspects: preconditions, payment flow, server-side validation. However, it lacks explicit mention of the return value format (though it implies a checkout URL). Adequate given the tool's complexity.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds minimal extra meaning beyond the schema (e.g., 'All three are required by the venue'), but does not significantly enhance parameter understanding.

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 'Book' and resource 'appointment slot at a venue (Wix Bookings)', distinguishing it from siblings like 'create_checkout' or 'request_reservation'.

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 directs to call 'get_availability' immediately before, explains the payment flow (returns checkout URL, nothing booked until payment), and instructs the user to open the link. Also notes that contact email is not verified.

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 mentions creating a URL for payment but lacks details on error handling, URL expiration, or what happens if items are invalid. Missing behavioral traits like 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?

Single sentence, front-loaded with action and result, no redundant words. 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?

No output schema, so description should explain return format. It only says 'creates a direct checkout URL' without specifying output structure or prerequisites like using list_products for product IDs.

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 descriptions for both productId and quantity. Description adds no extra meaning beyond 'one or more store products', 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 it creates a checkout URL for store products, specifying it's for Wix Stores. It differentiates from siblings like create_booking or list_products by focusing on payment checkout.

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 context that no login is required on the AI agent side, but does not explicitly state when to use versus alternatives like create_booking or list_products. No when-not guidance.

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

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

No annotations present, so description carries full burden. It discloses that slot times are in the venue's timezone, not necessarily the directory's. It implies a read-only operation. Could add more on error handling or output format, but sufficient for typical use.

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 wasted words. First sentence introduces purpose and context, second covers a key behavioral detail. Front-loaded and efficient.

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

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

No output schema, so description should cover return format but does not. However, for a 3-parameter tool with no enums and simple input, the description is reasonably complete. Could be improved by mentioning what the output contains (e.g., time slots).

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%, but description adds context: serviceId sourced from list_booking_services, date format confirmed, place_slug must match, and critical timezone nuance not in schema. Adds significant value beyond parameter names and types.

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 it gets available time slots for a bookable service on a given date, with specific reference to Wix Bookings. The verb and resource are precise, and it is distinguishable from sibling tools like create_booking or request_reservation.

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 how to use the tool: pass serviceId from list_booking_services, date in YYYY-MM-DD, and the same place_slug. It also warns about timezone behavior. Does not explicitly state when not to use, but context is strong enough.

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 cover behavioral traits. It explains the tool returns ticket names, prices, sale status, and remaining count. However, it does not disclose error handling (e.g., invalid slug), idempotency, or any required permissions. For a read-only operation, this is minimally adequate but could be more 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 consists of two concise sentences. The first states the core functionality, and the second explains the prerequisite and return data. No extraneous information is included.

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

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

Given the tool has one parameter and no output schema or annotations, the description covers purpose, input, and output sufficiently. It omits edge cases like error responses or rate limits, but for a simple read tool, this is acceptable.

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

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

The input schema already provides a description for the sole parameter (event_slug: 'Event slug from list_events.'). The description reinforces this by saying 'Pass the event slug from list_events,' adding no new semantic value. With 100% schema coverage, the baseline is 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 clearly states the tool's function: 'Get ticket types and prices for a specific event (Wix Events).' It identifies the resource (event tickets), the action (get), and the domain (Wix Events). This distinguishes it from sibling tools like list_events (which lists events) and reserve_event_tickets (which reserves tickets).

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 a clear prerequisite: 'Pass the event slug from list_events.' This instructs the user to first retrieve the slug using the list_events tool. While it doesn't explicitly state when not to use this tool or offer alternative tools, the context is sufficient for correct usage.

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

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

No annotations are provided, so the description carries full burden. It only describes positive return values but does not disclose side effects (e.g., authentication requirements, rate limits, behavior when no loyalty program exists).

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

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

The description is a single, well-structured sentence that immediately conveys the tool's purpose and return values. No extraneous 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, the description adequately covers return values (program name, points currency, tier structure). It is complete enough for a simple read-only tool, though it omits error scenarios.

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 (schema has empty properties, 100% coverage). The description does not need to add parameter info, and the baseline score for zero parameters 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 retrieves loyalty/rewards program details for a site, listing specific return fields (program name, points currency name, tier structure). It is distinct from sibling tools like get_site_info by focusing on loyalty 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?

No explicit guidance on when to use or not use this tool versus alternatives. The intended use is implied by the name and description, but there is no mention of prerequisites 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 are provided, so the description carries the full behavioral disclosure burden. It thoroughly describes the output (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood), implying a safe read operation. However, it does not explicitly state that it is read-only or mention any side effects, auth requirements, 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?

The description is concise (75 words) and front-loaded with the core purpose. It efficiently lists the returned fields without unnecessary elaboration, making it easy for an AI agent 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 low complexity (1 parameter, no output schema, no annotations), the description is complete. It fully communicates what the tool returns and how to call it, leaving no critical gaps for an AI agent to execute correctly.

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

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

The input schema has 100% description coverage for the single parameter 'slug', providing an example. The tool description does not add further semantic detail beyond what the schema already provides, so the parameter semantics are adequate but not enhanced.

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

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

The description clearly states the verb 'get', the resource 'full details for a specific place', and how to identify it via URL slug. It explicitly lists the included fields (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood), making it distinct from sibling tools like search_places or get_reviews.

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 that this tool should be used when you have a specific place's URL slug and need comprehensive details. However, it does not explicitly mention when to avoid it or provide alternatives for scenarios like searching places or getting only reviews.

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 describes the return content comprehensively but does not explicitly state that the tool is read-only or has no side effects. However, given the nature of the operation, this is acceptable and the description adds sufficient behavioral context.

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

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

The description is concise: two sentences. The first sentence delivers the core purpose and contents, and the second provides essential usage guidance. No redundant information.

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

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

Given the tool's simplicity (one required parameter, no nested objects, no output schema), the description is complete. It explains what the tool returns, how to use it, and the source for the input parameter. Nothing essential is missing.

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

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

The schema coverage is 100% and the description adds value beyond the schema by explaining how to obtain the place_slug value (e.g., 'from search_places or a place URL' with an example 'bar-do-ze'). This meaningfully aids the agent in selecting the correct 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: 'Get the food menu for a specific restaurant on this site.' It specifies what is returned (sections, dishes, descriptions, prices, dietary labels), making it distinct from sibling tools like search_dishes or get_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?

Explicit guidance is provided: 'Use search_places or list_categories first to find the restaurant's place_slug.' This tells the agent when to use this tool and what prerequisite steps are needed, effectively differentiating it from others.

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 only states return fields; lacks details on read-only nature, authorization, rate limits, or pagination behavior beyond the limit parameter.

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

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

Two concise sentences without unnecessary words. Front-loaded purpose and output details. Could be slightly improved by integrating parameter 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 simple read tool with one parameter, description covers basic purpose and output fields. Lacks details on default limit behavior, pagination, or ordering, but sufficient for basic 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 covers the limit parameter 100%. Description adds no additional meaning to the parameter, though it mentions output fields. 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?

Description clearly states it retrieves published reviews for the Wix Reviews site, explicitly listing the fields returned (reviewer name, rating, title, content). This is specific and distinguishes it from sibling tools like list_products 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?

No guidance on when to use this tool versus alternatives. Does not mention context, prerequisites, or conditions for appropriate 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. It describes output and prerequisite, but does not disclose potential side effects, permissions, or error behavior. Adequate for a read operation.

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

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

Two sentences, front-loaded with purpose, includes prerequisite. No unnecessary words. 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?

Describes output structure (cinemas, times, format, language) and prerequisites. Does not cover error handling or edge cases (e.g., no showtimes found), but is sufficient given simple tool and 100% schema coverage.

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% for both parameters. Description repeats information from schema (e.g., movie_slug example, date format/default) without adding new semantics. Baseline 3 applies.

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

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

Clearly states verb 'Get' and resource 'showtimes for a specific movie at cinemas in this neighborhood, for a given date.' Explains return fields (cinemas, times, format, language). No explicit differentiation from sibling tools, but purpose is 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?

Implied usage: when you need showtimes for a movie on a date. Mentions prerequisite 'Requires movies_enabled on this site.' but does not provide when-not-to-use or alternative tool names.

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 transparently discloses returned data (name, locale, time, weather). As a read-only tool with no side effects, it is adequately transparent.

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

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

The description is three sentences, front-loaded with the primary function, and contains no redundant information. 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 no parameters and no output schema, the description fully explains what the tool does and when to use it. It is complete for a simple read 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 tool has zero parameters; baseline is 4. The description adds value by explaining the return context, compensating for the lack of schema details.

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

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

The description clearly states the tool returns basic neighborhood directory info including local time and weather. It distinguishes itself from sibling tools like get_availability or create_booking, 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 says to use this tool for 'what time is it there' or 'what's the weather like' context, providing direct usage guidance. It lacks explicit when-not-to-use instructions, but the specificity is sufficient.

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

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

With no annotations provided, the description carries the full burden of disclosing behavior. It states the tool lists recent published posts and returns specific fields, implying read-only operation. However, it does not mention default behavior (e.g., sorting order, pagination), potential side effects, authentication needs, or error handling.

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, consisting of two sentences. The first sentence states the primary purpose, and the second lists the return fields. No unnecessary words or redundancy.

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

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

Given the absence of an output schema, the description compensates by listing the returned fields (title, excerpt, author, etc.). This provides sufficient context for understanding the tool's output. However, it omits information about default pagination, sorting order, and error conditions, preventing a perfect score.

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

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

The input schema already provides 100% coverage with descriptions for both parameters (limit and category). The tool description adds no additional parameter-level detail beyond what is in the schema. Per guidelines, baseline 3 applies when schema coverage is high.

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 action 'List' and the resource 'recent published blog posts for this site (Wix Blog)'. The mention of 'Wix Blog' distinguishes it from other sibling list tools like list_events or list_products. The description also lists the returned fields, leaving no ambiguity about the tool's output.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of prerequisites, when not to use it, or comparison with related tools such as list_categories or search functions.

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?

Despite no annotations, the description discloses key behaviors: services are listed for every venue, even those without online booking; the bookableViaMcp field and its implications (null id, alternative booking method). It covers return fields and edge cases, though it omits details on rate limits or pagination, which are not critical for this read-only tool.

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

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

The description is a single, information-dense paragraph that front-loads the purpose. While it is concise and every sentence adds value, a bulleted structure could improve readability. No wasted words.

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

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

With no output schema, the description fully explains return fields (name, description, price, duration, bookableViaMcp) and covers edge cases (non-bookable venues, directory vs venue services). For a list tool with one parameter, this is comprehensive and leaves 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?

Input schema has one optional parameter with good description (100% coverage). The description adds value by explaining the source (from search_places), the two outcomes, and that serviceId from this form works with create_booking, enhancing the semantic meaning beyond the schema.

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

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

Description clearly states 'List a venue's services — what it offers, with price and duration.' It specifies the verb 'list', the resource 'venue's services', and distinguishes between the two modes (with and without place_slug), effectively differentiating from sibling tools like get_availability and create_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?

Explicitly explains when to use each form: 'pass place_slug... that is what you want in almost every case' and omitting it lists directory services 'which most sites do not have.' Provides clear context and alternatives, such as using bookingUrl when bookableViaMcp is false.

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

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

No annotations are provided, so the description carries the full burden. It states 'returns' implying a read operation, but does not explicitly confirm it's non-destructive or disclose any behavioral traits like rate limits or prerequisites. 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 a single, well-structured sentence that is front-loaded with the main purpose. No unnecessary words; every part 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?

Given no parameters, no output schema, and no annotations, the description gives a solid overview of the response content. It lists key elements but could be more detailed about the response structure. Still, it provides sufficient context for the agent.

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

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

With zero parameters, the baseline is 4. The description adds value by explaining the tool's output, which goes beyond the empty schema. It provides meaningful context about what the tool returns.

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 the full category taxonomy, specifying components like top-level groups, subcategories, localized labels, schema.org types, and live place counts. It distinguishes from sibling list_* tools by focusing on category taxonomy.

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

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

The description implies use for getting category taxonomy but does not explicitly state when to use it vs alternatives or provide any exclusion criteria. Sibling tools suggest this is for directory structure, but no direct guidelines are given.

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

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

No annotations are provided, so the description carries the full burden. It discloses that weather forecasts are included for events within 7 days and that 'agora' filter is resolved live. However, it does not mention whether the tool is read-only, rate limits, or authentication requirements.

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

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

The description is two sentences with no fluff. The first sentence states the core purpose, and the second adds critical detail about weather and live filtering. 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 3 optional parameters, no required ones, and no output schema, the description covers the return fields, special weather data, and filter usage. It is nearly complete, though it could mention ordering (e.g., by date) or potential pagination beyond the limit parameter.

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%, but the description adds context beyond the schema: it explains how weatherForecast can be used (e.g., 'it will be raining'), gives examples for filter values, and clarifies the behavior of 'upcoming_only' (default true). This goes beyond the baseline of 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 clearly states it 'list upcoming events in this neighborhood' with specific fields (date, venue, price, URL) and a weather forecast for events within 7 days. It distinguishes from sibling list tools by focusing on events and providing detailed filter options.

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 when to use the filter parameter (e.g., 'agora' for live events) and highlights that it is resolved live. However, it does not explicitly exclude this tool for booking or other transactional tasks, which are handled by sibling tools like create_booking or reserve_event_tickets.

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 that the tool returns all FAQs grouped by category, which is sufficient for a simple read-only operation. No annotations are provided, so the description carries the burden, but it lacks details about potential limitations (e.g., if the site has no FAQs or if there are 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 efficient sentences: the first states the action and resource, the second gives usage guidance. No waste, perfectly front-loaded.

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

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

The description is complete for a simple list tool with no parameters, no output schema, and no annotations. It adequately covers what the tool returns and when to use it, though it could note that it returns all FAQs without filtering options.

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, so the description doesn't need to explain them. It adds value by describing the output structure (grouped by category) and providing usage examples, which compensates for the lack of parameters.

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

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

The description clearly states the tool's purpose: to retrieve all FAQ questions and answers for the site, grouped by category. It also gives specific examples of content (opening hours, parking, policies), making it highly specific and distinguishable from sibling tools.

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

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

The description explicitly says 'Use this to answer common questions about the site', providing strong context for when to invoke the tool. However, it does not mention when not to use it or alternatives, which would improve clarity.

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. Description discloses return values (form name, ID, field definitions). Does not mention safety/destructive nature, but as a list tool, behavioral expectations are clear.

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 returns, then usage guidance. 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?

No output schema, but description enumerates returned fields (name, ID, field definitions with label, type, required). Adequate for an agent to understand what to expect.

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

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

Input schema has no parameters (0 required, empty properties). Schema coverage is 100%. Baseline 4 for 0 params; description adds no further param info but none needed.

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

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

Description clearly states 'List available contact/signup forms' with verb 'list' and resource 'forms'. Distinguishes from sibling tools like submit_form.

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

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

Explicitly says 'Use before submit_form to discover which fields to fill.' Provides clear context for when to use this tool versus 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 are provided, so the description must fully disclose behavior. It states the output contains ranked places with editorial notes, but does not mention read-only nature, authentication needs, or pagination behavior. 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?

Two succinct sentences: first defines the tool's purpose and output, second provides usage context. 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 list tool with no output schema, the description gives enough context (ranked places, editorial notes). It could mention limit or pagination but is adequate for the tool's complexity.

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

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

There is only one parameter (limit) with 100% schema coverage. The description does not add any meaning beyond the schema's description of default/max values. Baseline 3 is appropriate.

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

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

The description clearly states the tool lists 'curated editorial guides' (best-of lists) with ranked places and editorial notes. It distinguishes from sibling tools like list_blog_posts and list_categories by specifying the curated, ranked nature.

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 recommends this tool for 'best X in this neighborhood' questions, giving clear context. However, it does not mention when not to use it or explicitly exclude alternatives like search_places.

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

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

No annotations are provided, so the description bears full responsibility. It discloses that the tool only works on sites with movies_enabled, and details the return categories (now-showing with showtimes, coming-soon, streaming). It adds value beyond the schema by explaining the behavior of the 'status' parameter.

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

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

The description is two sentences, no filler. First sentence sets scope and condition, second sentence enumerates return categories and included fields. 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?

Given the tool has only 2 optional parameters and no output schema, the description explains the return fields (title, genres, TMDB rating, runtime, detail URL). It is nearly complete, though missing default ordering or pagination details.

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

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

Schema coverage is 100%, and both parameters have descriptions in the schema. The description adds extra context for the 'status' enum values, explaining what each means (e.g., 'now_showing' = films with upcoming showtimes). This adds value beyond the bare 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 movies available in the neighborhood, with three categories (now-showing, coming-soon, streaming). It specifies the resource (movies) and action (list), and distinguishes from siblings 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 provides a clear purpose but does not explicitly state when to use this tool versus alternatives like list_events or get_showtimes. The usage context is implied but lacks direct exclusions or comparisons.

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

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

With no annotations, the description carries the full burden. It discloses the returned fields and the special behavior of FLASH offers (countdown deadline). However, it omits details like default ordering, pagination, or whether expired offers are automatically excluded.

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 purpose and key details. No fluff, but could be slightly more structured (e.g., bullet points for return fields).

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 covers core behavior well. It lacks details on default limit, pagination, and ordering, but these are minor omissions for a straightforward 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?

Schema coverage is 100%, so baseline is 3. The description mentions FLASH offers, which aligns with the kind parameter's enum, but adds no additional semantic value beyond what the schema provides.

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

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

The description clearly states the tool lists active promotions and deals in a neighborhood directory, specifies returned fields, and distinguishes FLASH offers from standard ones. It differentiates from sibling listing tools by focusing on offers.

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 listing deals but does not explicitly state when not to use it or mention alternatives. Given many sibling listing tools, some guidance on when to prefer this over list_products or list_events would improve clarity.

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 return fields and the two modes of operation. While it implicitly suggests read-only behavior, it does not explicitly state non-destructiveness, but the context 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?

The description is concise (3 sentences), front-loaded with the verb and resource, uses line breaks for readability, and every sentence provides essential information without redundancy.

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

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

Given the tool's simplicity (1 optional parameter, no output schema), the description fully covers input, output fields, behavior, and cross-references. No gaps remain.

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

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

The schema already describes the parameter with 100% coverage, but the description adds critical context: it recommends using the parameter and explains the behavioral difference when omitted. This adds significant value beyond the schema.

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

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

The description clearly states it lists membership or subscription plans, specifies the resource (Wix Pricing Plans), and distinguishes between two use cases based on the presence of place_slug. This differentiates it from sibling tools and is 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 explicitly recommends using place_slug from search_places for venue plans, and explains that omitting it yields the directory's own plans (which most sites lack). This provides clear when-to-use guidance and references a prerequisite sibling tool.

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

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

No annotations provided, so description must fully disclose behavior. It only states it lists products and returns certain fields. It does not mention that it is read-only, any authentication needs, rate limits, pagination behavior, or side effects.

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

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

Very concise single sentence. No wasted words, but could be expanded slightly without losing conciseness to cover usage or behavioral 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?

Adequate for listing a simple set of products with two optional parameters. However, lacking usage guidance and behavioral details for a tool with many siblings. No output schema so description should elaborate on return format but does not.

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 clear parameter descriptions. The description adds no additional meaning beyond the schema for the parameters, but the baseline score applies as the schema already carries the burden.

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 it lists products in a Wix Stores site and specifies the returned fields (name, price, stock status, product type). This clearly differentiates it from sibling tools like list_blog_posts or list_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?

No guidance on when to use this tool vs alternatives, such as when to use search queries or filtering. No mention of when not to use it or prerequisites like site configuration.

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 fields (name, profile URL, category, metadata) but does not mention pagination, sorting, rate limits, or authentication. It is reasonable for a list operation but not comprehensive.

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

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

Two sentences, front-loaded with the core function, no redundant information. 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?

For a simple list tool with one optional parameter and no output schema, the description adequately covers what it does and returns. Missing details like ordering or pagination could be included but are 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?

Parameter 'limit' is fully described in the schema (100% coverage), so baseline is 3. The description adds no extra information about the parameter beyond what the schema provides.

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

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

The description clearly states the tool lists solo service-provider profiles without a fixed physical location, with specific examples (dog walkers, tutors, personal trainers). It distinguishes from sibling tools that list other entities (products, events, movies, etc.). The verb 'list' and resource 'profiles' are 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 provides clear scope and examples, implying when to use this tool, but does not explicitly state when not to use it or mention alternative tools (e.g., search_places) for broader searches. The context is clear but lacks 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 critical behaviors: request is held, email sent with link, link expiry, restaurant not notified until link clicked, and that this is not a confirmed 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?

Informative paragraph without fluff. Could be more structured (e.g., bullet points for key warnings) but remains clear and concise.

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 exists, so description should explain response. It notes the link is not returned but does not describe what the response contains (e.g., a confirmation ID). Leaves 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?

Schema coverage is 100% with descriptions, so baseline is 3. The description adds value by clarifying email purpose and the non-return of the confirmation link, beyond 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 requests a table, explaining it is not a confirmed booking. It distinguishes from a confirmed booking by noting the out-of-band confirmation, but does not explicitly differentiate from sibling 'create_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 instructions: tell user to check inbox, use real email, link expires in 24 hours. Does not directly compare to siblings like 'create_booking' or 'get_availability'.

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 key behaviors: the hold is temporary and unpaid, tickets are not claimed until checkout completes, hold expires automatically, and works only for Wix Events. This goes beyond the input schema.

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

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

The description is two sentences: the first states the main action and result; the second (in caps) highlights critical temporary nature and scope. No wasted words, front-loaded with key 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?

No output schema is provided, but the description states it returns a checkout URL, which is sufficient for the agent to understand the response. The description covers the tool's purpose, constraints, and failure conditions (external events). Could briefly mention how to detect expiration, but overall complete for a reservation tool.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds context about the hold mechanism and limits (max 10 tickets/ticket types), which adds value beyond the schema descriptions. It does not repeat parameter details but complements them with behavioral context.

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

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

The description uses specific verbs ('Hold tickets', 'return a checkout URL') and clearly states the tool is for reserving event tickets sold through Wix Events, distinguishing it from external event platforms mentioned in the sibling tools.

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

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

The description explicitly states when to use (events sold through this site) and when not (events sold elsewhere like Sympla, Ingresse, Sesc), and provides the alternative of using the event's own ticketUrl. It also includes constraints (max 10 tickets, 10 ticket types) and explains the temporary nature of the hold.

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 behavior: nobody on guest list, confirmation email sent, RSVP only upon link click, 24-hour expiry, and that the link is not returned. This is excellent transparency.

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

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

The description is a single paragraph with clear, front-loaded sentences. Each sentence adds value without excessive length, though minor restructuring could improve scannability.

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 4 params, no output schema, and no annotations, the description comprehensively covers purpose, behavior, parameter context, and user instructions, leaving no gaps for an AI agent.

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

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

Schema coverage is 100% (baseline 3). The description adds meaningful context beyond schema by explaining the email's role ('confirmation link is sent here') and overall flow, enhancing parameter understanding.

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 starts with 'RSVP to a free event on this site (Wix Events)', which uses a specific verb and resource, clearly distinguishing it from sibling tools like reserve_event_tickets for paid 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 provides explicit instructions: 'Tell the user to check their inbox' and 'Use a real address belonging to the person you are acting for'. It also explains the confirmation flow, aiding appropriate 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the search covers all restaurants, groups results by dish, and returns price, description, dietary labels, and place URL. It does not mention pagination or ordering, but the information is sufficient for an agent.

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 well-structured: two sentences that front-load the purpose and follow with details. Every sentence adds value without redundancy.

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

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

Despite no output schema, the description explains the return structure (restaurants with price, description, dietary labels, place URL). It covers both use cases (with and without query), making it 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?

The input schema has 100% coverage with descriptions for both parameters. The description adds value by providing examples ('feijoada', 'pizza margherita') and explaining the effect of omitting query (list top dishes). This goes beyond the schema.

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

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

The description clearly states the tool's purpose: 'Find which restaurants serve a dish in this neighborhood.' It specifies the action (search), resource (dishes), and grouping (by dish). It distinguishes from sibling tools like search_places and get_restaurant_menus by being dish-centric.

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: 'Use this for any "where can I eat X" question.' It also explains the behavior when query is omitted (list top dishes). While it does not explicitly mention when not to use, the context and sibling names make it 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?

With no annotations, the description carries full burden. It transparently discloses: accent-insensitive and typo-tolerant matching, ranking by relevance, server-side open_now computation, ALL-matched attributes, and result fields including precomputed booleans and structured hours. It omits error handling and rate limits but is highly informative for a search tool.

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

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

The description is concise yet thorough, covering purpose, matching, filters, and result fields in a logical order. It front-loads the primary use and then detail. At ~300 words, it avoids verbosity while packing necessary information. Minor redundancy could be trimmed, but overall 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?

With no output schema, the description adequately explains key result fields (open_now, attributes, delivery, rating, hours). It covers all six input parameters with behavioral context. Missing details like pagination, default limit, or error responses are tolerable for a search tool but could be added for full completeness.

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

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

Schema coverage is 100%, providing a baseline of 3. The description adds significant value: it explains `q` matching effects (typo-tolerance), `open_now` as current local time, `attributes` as slugs requiring ALL match, and lists common amenity slugs with examples. This exceeds schema descriptions and aids correct usage.

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

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

The description clearly states the tool searches for places (restaurants, cafes, shops) in a neighborhood, using specific verbs and examples. It implicitly distinguishes from siblings like 'search_dishes' by focusing on places and offering multi-condition filters with unique features (typo-tolerance, amenity slugs).

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 ('Compose filters for multi-condition queries') and mentions matching behavior, but does not explicitly guide when to use this tool vs alternatives (e.g., 'get_place' for a single place, 'search_dishes' for dishes). No when-not or exclusionary advice is given.

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

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

No annotations provided, so description bears full burden. It discloses the action (submission) and return (submissionId), but lacks details on side effects, permissions, or error handling. 'On behalf of the user' hints at auth but is insufficient for a mutation 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?

Two sentences, no fluff. Front-loaded with the primary action, then provides critical prerequisite and return info. 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?

Given the simple two-parameter schema and no output schema, the description covers all essential aspects: main action, prerequisite workflow, and success return. It is complete for an agent to invoke 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 descriptions, so baseline is 3. The description adds value by explaining the origin of parameter values (from list_forms) and the success return (submissionId), enhancing understanding beyond the schema.

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

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

The description clearly states the action: 'Submit a form on behalf of the user (Wix Forms).' It uses a specific verb ('Submit') and resource ('form'), and distinguishes from siblings by mentioning list_forms as a prerequisite.

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 call list_forms first to obtain formId and field keys, providing a clear when-to-use and prerequisite. No alternatives are mentioned, but the context is unambiguous.

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