Gracie Barra Jiu-Jitsu

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

Since no annotations exist, the description fully discloses critical behavior: 'NOTHING IS BOOKED UNTIL THE CUSTOMER PAYS', returns a checkout URL, slot stays off calendar, and contact email is not verified. This is comprehensive 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?

Description is four sentences with a bold front-loaded warning. Each sentence provides essential information without redundancy. Structured for quick scanning by an AI agent.

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

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

Given no output schema, the description explains the key return (checkout URL) and the non-booking until payment. It covers prerequisites and post-conditions. Minor gap: no mention of error handling or rate limits, but overall complete for this complex 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%, but the description adds significant context: for contact parameters it states 'All three are required by the venue', for startDate/endDate it references get_availability, and for serviceId it references list_booking_services. This greatly aids correct invocation.

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 a clear verb+resource: 'Book an appointment slot at a venue.' It distinguishes itself from sibling tools by mandating a call to get_availability beforehand and explaining that the booking is not final until payment.

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 usage guidance: 'Call get_availability immediately before this' and explanation that slot re-validation occurs server-side. Also advises telling the user to open the checkout URL. Provides clear when-to-use and prerequisites.

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 disclosure burden. It explains that the tool creates a URL for user payment and that no agent login is needed, but lacks details on auth, rate limits, or side effects like inventory reservation.

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, efficiently conveying the core purpose and a key behavioral trait.

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?

There is no output schema, yet the description does not explain what the tool returns (the URL), nor does it mention potential limitations like URL expiry. Additional context would improve completeness.

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

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

The input schema has 100% description coverage for all parameters, so the description adds no new parameter details beyond stating 'one or more store products,' which aligns with 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 creates a direct checkout URL for one or more store products, specifies the resource (Wix Stores), and distinguishes itself from sibling tools focused on listing or other actions.

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 indicates no login required on the AI agent side, but it does not explicitly state when to use this tool versus alternatives, or identify prerequisites like needing product IDs from list_products.

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 behavioral disclosure burden. It discloses that slot times are returned in the venue's timezone, which is critical. It implies read-only behavior. It does not cover auth needs, rate limits, or edge cases like no slots 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 two sentences, front-loaded with the purpose. Every sentence adds unique information without redundancy. It is concise 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?

The tool has 3 parameters (2 required) and no output schema. The description adequately covers parameter usage and the timezone aspect. However, it does not describe the return format, leaving the agent to infer what the available slots look like.

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 meaningful context: tying serviceId and place_slug to list_booking_services, and explaining the timezone implication of place_slug. This adds value beyond the schema descriptions, though it does not detail place_slug's exact format.

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 available time slots for a bookable service on a given date, specifying the domain (Wix Bookings) and naming the resource. It implicitly distinguishes from siblings like list_booking_services by focusing on availability, but does not explicitly differentiate from create_booking or similar tools.

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

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

The description provides the when-to-use context: pass serviceId from list_booking_services, date in YYYY-MM-DD, and same place_slug. It includes a timezone caveat. However, it does not mention when not to use or suggest alternatives, leaving the agent to infer from sibling 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?

Without annotations, the description carries the burden. It discloses the return content (ticket names, prices, sale status, remaining count) and the event source. However, it does not explicitly state that the operation is non-destructive or mention any potential side effects, rate limits, or authentication needs, which would be helpful.

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 defines the tool's purpose and context, the second provides usage guidance. No extraneous information, front-loading the key action and returned data.

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

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

For a simple tool with one parameter and no output schema, the description covers the essential: what it does, required input, and return type. It lacks mention of pagination or limits, but these are not typical for a ticket listing. Overall sufficient 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?

The schema description for event_slug is 'Event slug from list_events,' and the description reiterates this. With 100% schema coverage, the baseline is 3. The description adds minimal extra context (explicitly stating the source), but does not introduce new parameter semantics 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 retrieves ticket types and prices for a specific event in Wix Events. It specifies the returned data (ticket names, prices, sale status, and count) and differentiates from sibling tools like reserve_event_tickets by focusing on read-only retrieval.

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 instructs to pass the event slug from list_events, establishing a clear precondition and workflow. While it doesn't explicitly state when not to use it, the read-only nature and context are clear, and no alternatives are noted.

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 only lists return fields. Fails to disclose if there are side effects, permissions needed, or constraints (e.g., site must have loyalty enabled).

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 superfluous words. Front-loaded with the action and resource, then lists returned data. Efficient.

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

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

Given no output schema and no parameters, description adequately specifies return fields. However, lacks context about when this tool applies (e.g., only if site has loyalty) and any error conditions.

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 input schema (0 params). Baseline score of 4 applies per guidelines since description does not need to describe 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?

Description clearly states it retrieves loyalty/rewards program details for the site, and specifies exact return fields (program name, points currency, tier structure). Disambiguates from sibling tools by naming 'Wix Loyalty'.

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, or any prerequisites. Sibling tools exist but none cover loyalty, so explicit usage context would help.

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 carry full burden. Discloses return fields but does not mention error cases, authentication, rate limits, or any side effects. Adequate but not rich.

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

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

Single sentence, fully front-loaded with essential information. No unnecessary words. 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?

Despite no output schema, description lists key return fields. For a simple get-by-ID tool with one parameter and no annotations, it is fairly complete. Could mention potential error responses or authorization.

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

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

Schema coverage is 100% with a clear parameter description. The tool description adds context by explaining that slug is a URL slug and providing an example, enriching 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?

Clearly states the action ('Get full details'), the resource ('place'), and the key ('by its URL slug'). Lists specific data returned (opening hours, ratings, etc.). Distinguishes from siblings like 'search_places'.

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 vs alternatives. Implied by name and description that it's for fetching a single place by slug, but no direct comparison to siblings 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 carries full burden. It discloses the return content but does not mention side effects, authentication, or rate limits. It implies read-only behavior, which is adequate for a data retrieval 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 with no unnecessary words. The first sentence states the purpose and return data; the second provides usage instructions. 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?

Despite lack of output schema, the description adequately explains the return data. It also includes prerequisite tools. For a simple one-parameter tool, this is complete 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 coverage is 100% with one parameter. The description adds value by providing an example slug and mentioning the source of the slug (search_places or place URL), enhancing the schema's brief 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 it gets the food menu for a specific restaurant, listing the specific data returned (sections, dishes, prices, dietary labels). It distinguishes from sibling tools by directing users to first use search_places or list_categories to find the place_slug.

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 place_slug, providing clear usage context. However, no explicit exclusion of alternative tools like search_dishes is mentioned.

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

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

No annotations are provided, so the description must fully convey behavioral traits. It states it 'gets' reviews and returns specific fields, implying a read-only operation, but does not explicitly confirm safety (e.g., no mutation, no destructive side effects). There is no mention of authentication, rate limits, or pagination. For a tool with no annotations, this is insufficient.

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. It is front-loaded with the key action and resource, and every word adds value. No unnecessary details.

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 optional parameter, no output schema, no nested objects), the description is relatively complete. However, it could mention ordering (e.g., 'latest reviews') or that only approved/published reviews are returned. It does not state whether the limit parameter affects the order or if pagination exists. For a list tool, this missing context slightly reduces 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 description coverage is 100% with one optional parameter ('limit'). The input schema already describes the parameter's purpose, default (10), and max (50). The tool description adds no additional context beyond the schema, 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 the action 'Get' and the resource 'published reviews for this site (Wix Reviews)'. It lists the return fields (reviewer name, rating, title, content). While it doesn't explicitly differentiate from sibling tools, the specificity of 'reviews' and the mention of Wix Reviews provide sufficient context for purpose clarity.

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 lacks any guidance on when to use this tool versus alternatives. No exclusions, prerequisites, or context for appropriate use are provided. Given the many sibling tools, this omission makes it harder for an AI agent to select the correct tool without additional trial and error.

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

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

With no annotations provided, the description carries the full burden. It mentions the requirement 'movies_enabled' and implicitly describes a read operation. However, it does not disclose potential caching behavior, rate limits, or side effects. Still, the description is adequate for a simple data retrieval tool.

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

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

The description is two sentences long, directly stating the tool's purpose and a key requirement. No fluff; 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?

Given the tool has no output schema and no annotations, the description covers what it returns (cinemas, times, format, language) and a prerequisite. For a simple query tool, this is 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 description coverage is 100% with both parameters described. The description adds context: 'date' defaults to today (BRT) and 'movie_slug' comes from list_movies with an example. This goes 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 uses specific verbs and nouns: 'get showtimes for a specific movie at cinemas in this neighborhood, for a given date'. It clearly distinguishes from sibling tools like list_movies (which lists movies, not showtimes) and get_availability (which likely covers other resources).

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 states a precondition: 'Requires movies_enabled on this site.' It does not explicitly mention when not to use or alternatives, but the context is sufficient for selecting this tool over siblings. A slight deduction for lack of explicit 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 full burden. It discloses the returned data (name, locale, domain, canonical URLs, local time, current weather). It implies no side effects or auth requirements, which is appropriate for a read-only tool. Could mention update frequency of weather, but 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?

Two sentences, each earning its place. First sentence lists what's returned; second provides usage context. 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?

Given no output schema and zero parameters, the description is complete enough. It covers the key outputs. Could optionally specify format for time/weather, 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?

No parameters, so baseline is 4. The schema coverage is 100% with empty properties. The description adds value by detailing the response contents.

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

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

The description uses the verb 'Returns' and specifies the resource: 'basic information about this neighborhood directory'. It lists specific items (name, locale, domain, local time, weather) and is clearly distinct from sibling tools like 'get_place' 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?

Explicitly states when to use: 'Use this for any "what time is it there" or "what's the weather like" context.' This provides clear guidance and excludes 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?

No annotations provided, so description carries full burden. States it returns specific fields (title, excerpt, etc.) but doesn't mention ordering, pagination, or any side effects. Sufficient for a simple read tool.

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

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

Single clear sentence. Could benefit from structure but 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?

Lists return fields compensating for lack of output schema. Simple tool with only 2 optional parameters; description is largely adequate.

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, both parameters described. Description adds no additional parameter insight 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?

Clearly states the tool lists recent published blog posts for Wix Blog. Distinct from all sibling tools as no other blog-related tool exists.

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 any exclusions or prerequisites.

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 services are listed for every venue, including non-bookable ones, and explains the bookableViaMcp field. Behavior when place_slug is omitted is also clearly described.

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 few sentences but well-structured and front-loaded with the main action. Every sentence adds value, though it could be slightly trimmed without losing clarity.

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 one optional parameter and no output schema, the description compensates by explaining return fields and the key bookableViaMcp flag. It covers main use case and edge cases, though minor details like ordering are omitted.

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, but the description adds significant context: when to use the parameter, what happens without it, and its relationship to search_places. This enriches the parameter semantics beyond the schema definition.

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. It specifies the verb 'list' and the resource 'services', and distinguishes from siblings by focusing on venue-specific services, unlike other list tools such as list_products 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?

Explicit guidance is provided: 'Pass place_slug (from search_places) to list the services of a specific VENUE... that is what you want in almost every case.' It explains when to omit the parameter, what happens, and how it works with create_booking, offering clear 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?

No annotations provided, so description carries burden. It describes return content but lacks behavioral traits like read-only nature, caching, rate limits, or error conditions. Adequate for a simple 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?

Single sentence with clear, front-loaded language. Every part adds value: returns taxonomy, details included. 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?

Complete for a zero-parameter, no-output-schema tool. Describes return content adequately. Could mention if taxonomy is static or request-specific, but not necessary.

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, schema coverage 100%. Baseline 4 applies; description adds no parameter information, which is acceptable.

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 returns the full category taxonomy with specific details (top-level groups, subcategories, localized labels, schema.org types, live place counts). This distinguishes it from other list_* sibling tools.

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

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

Implied usage (need category taxonomy), but no explicit when-to-use, when-not-to-use, or alternatives. No comparison to siblings like list_products.

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 discloses key behaviors: weather forecast for nearby events, live resolution for `'agora'`, and exclusions for season runs. It does not mention read-only nature but inference is 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 packed with essential information. No wasted words, effectively front-loaded with key features and parameter 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?

Given no output schema, the description mentions return fields. It could be more explicit about event structure, but overall covers key aspects like weather and filter semantics.

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 value by explaining the behavior of filter values beyond enum descriptions, such as live resolution and exclusions. The `upcoming_only` parameter gets no extra context 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 it lists upcoming events with specific fields (date, venue, price, URL) in a neighborhood, and adds a unique weatherForecast feature. This distinguishes it from sibling tools like get_event_tickets or list_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?

Provides explicit guidance on using the `filter` parameter, especially `'agora'` for live resolution. However, it does not explicitly state when to use this tool over alternatives like `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?

No annotations, but description clearly indicates it returns all FAQs grouped by category; could mention if there are any limitations like pagination or unpublished items, but otherwise transparent.

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

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

Two concise sentences with no extraneous information; efficient and front-loaded.

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

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

Given no parameters and no output schema, description provides sufficient context (what it returns, grouping, use cases). Could improve by mentioning data structure, but adequate.

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; schema coverage is 100%. The baseline for 0 params is 4, and description adds no parameter info, which is appropriate.

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

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

Clearly states it retrieves all FAQ Q&A grouped by category, with examples of use (opening hours, parking, policies), distinguishing it from sibling list tools like 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?

Explicitly says to use it to answer common questions and gives examples, but doesn't provide when-not-to-use or alternatives, though context makes 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?

No annotations provided, so description carries full burden. It accurately describes the tool as listing forms and returning specific data, implying a non-mutating operation. Minor lack of detail on authorization or side effects, but appropriate for a list 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 with no wasted words. Purpose is front-loaded and 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?

Given no output schema, the description adequately details the return content and usage context. It is complete for understanding the tool's purpose and output.

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 (100% coverage), so baseline is 3. Description adds value by specifying what the list returns (form name, ID, field definitions), enhancing the empty 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 available contact/signup forms with details like name, ID, and field definitions. It uses specific verb 'list' and resource 'forms', distinguishing it from other list_* sibling tools.

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

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

Explicitly states 'Use before submit_form to discover which fields to fill', providing clear context on when to use this tool relative to a 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 carries full burden. Describes read-only behavior implicitly ('list'), but does not explicitly state non-destructive nature, auth needs, or edge cases. Adequate 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 concise sentences, front-loaded with purpose, no wasted words. Efficient and to the point.

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 fully informs the agent about the tool's output (ranked places with editorial notes) and ideal use case. 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?

Only one parameter (limit) with 100% schema coverage. The description does not add meaning beyond what the schema already provides (default, max). 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 the tool lists curated editorial guides with ranked places and editorial notes. Differentiates from sibling list tools by specifying 'best of' lists and providing a use case ('best X in this neighborhood').

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?

Identifies a specific use case ('best source for best X in this neighborhood questions'), implying when to use. Does not explicitly state when not to use or compare with 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 must disclose behavior. It mentions the tool returns specific movie information and is contingent on movies_enabled, but does not explicitly state it is a read-only operation, mention rate limits, or authentication requirements. The behavior is adequately implied but not fully 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 two sentences with no unnecessary words. The first sentence states the core purpose with a condition, and the second lists the return content. It is 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?

For a two-parameter list operation without an output schema, the description adequately covers the tool's domain (neighborhood movies), required preconditions (movies_enabled), available filters (status), and return fields. It is sufficiently complete for an agent to understand when and how to invoke the tool.

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

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

Schema coverage is 100%, but the description adds significant context to the status parameter by defining each enum value (e.g., 'now_showing' = films with upcoming showtimes). This enhances an agent's understanding beyond the schema's brief descriptions. The limit parameter description matches 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 specifies the tool lists movies available in the neighborhood, restricted to sites with movies_enabled. It details the categories (now-showing, coming-soon, streaming) and included fields (title, genres, TMDB rating, runtime, detail URL). This distinctively identifies its purpose among sibling tools like list_events or list_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 provides clear context (neighborhood, movies_enabled) and explains each status filter value, helping the agent decide when to use each. However, it does not explicitly state when not to use this tool or compare it with alternativelist tools from siblings.

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

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

With no annotations, the description carries the burden. It explains return fields and adds a special note about FLASH offers having countdown deadlines. It does not mention destructive or auth-related behavior, but as a 'list' tool, it's inherently read-only, and the information provided 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 concise sentences with front-loaded purpose. Every sentence adds value: purpose, return fields, special note on FLASH offers. 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?

Given no output schema, the description compensates by listing return fields. It covers the two parameters, but lacks details on pagination or ordering. Still, it's fairly complete for a simple 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?

Schema coverage is 100% with both parameters described. The description reinforces the 'kind' parameter by mentioning FLASH offers in the return context, but adds no new syntactic details. 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 'List active promotions and deals' with specific verb 'List' and resource ('promotions and deals'). It distinguishes from sibling list tools by focusing on offers with return fields like discount label, promo code, etc. No ambiguity.

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 for browsing promotions, but no explicit when-to-use or alternatives among siblings like list_pricing_plans or list_products. Lacks context for when not to use this tool.

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

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

No annotations are provided, so the description must carry the burden. 'List' implies a read-only operation, but there is no explicit statement about non-destructive behavior, idempotency, or rate limits. The description is adequate but could be improved by confirming this tool does not modify data.

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, front-loaded with the action and resource, and tightly packs all relevant information without unnecessary words. Every part 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 (no parameters, no output schema), the description is complete: it identifies the resource, lists return fields, and clarifies the site context. It covers all essential aspects for an agent to select and invoke this 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?

The tool has zero parameters, so the input schema is trivial and coverage is 100%. Per the baseline rule for 0 parameters, a score of 4 is appropriate. The description adds no parameter info (none needed), but it does describe the return fields, which adds 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 explicitly states the action ('List'), the resource ('membership or subscription plans'), and the scope ('this site (Wix Pricing Plans)'). It also lists specific return fields (plan name, price, billing cycle, perks, checkout URL), making the tool's purpose clear and distinct from sibling tools like list_products or list_booking_services.

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. It is a simple listing tool without parameters, so context is minimal, but among many sibling tools, some indication of when to use this particular listing (e.g., for pricing plans specifically) would be helpful.

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 return fields but lacks details on pagination, ordering, filtering beyond the schema, and whether it includes hidden/out-of-stock items. The read-only nature is implied but not stated.

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

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

Two sentences, no fluff, front-loaded with action 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 output schema, the description covers return fields. However, it omits details on pagination behavior (despite limit parameter) and response structure. Still, it is largely complete for a simple 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?

Schema coverage is 100% with descriptions for both parameters. The tool description does not add meaning beyond what the schema provides, 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?

Clearly states it lists products in the site's store (Wix Stores) and mentions the return fields (name, price, stock status, product type). Distinguishes from sibling tools like list_blog_posts and 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?

Implies usage for listing store products but does not explicitly state when to use or when not to use. No guidance on alternatives or prerequisites.

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

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

With no annotations provided, the description carries the full burden for behavioral transparency. It discloses return fields (name, profile URL, category, and available metadata like age, height) but lacks information on ordering, pagination (only a limit parameter is in schema), or any effects on the system. The description adds some value but is 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 two sentences, front-loaded with the purpose, and includes concrete examples. Every word contributes 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?

Given the tool's simplicity (one optional parameter, no output schema), the description covers the essential purpose and return data. It does not detail edge cases or behavior like default limits, but is sufficient for most agents 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 input schema has 100% description coverage (the 'limit' parameter is described as 'Max profiles to return (default 50)'). The tool description does not add any additional meaning to the parameter, so the baseline score of 3 applies.

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

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

The description clearly states the verb 'List' and the resource 'solo service-provider profiles on this site'. It further distinguishes this tool from siblings by specifying the type of profiles: businesses without a fixed physical location, with examples like dog walkers, tutors, personal trainers.

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

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

The description provides clear context for when to use this tool: to list solo service-provider profiles that lack a fixed location. However, it does not explicitly state when not to use it or mention alternative tools, though the specificity helps differentiate it from sibling listing tools.

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

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

No annotations are provided, so the description fully discloses the behavior: the request is not immediately sent to the restaurant, a confirmation email with a 24-hour expiry link is sent, and confirmation is out-of-band. This is comprehensive and 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 concise, front-loading the purpose and then providing key behavioral notes in short, clear sentences. 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?

Despite lacking an output schema, the description covers the complete user flow, including post-request steps (check inbox, click link). It addresses potential user confusion about the tool's outcome, making it fully informative.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional parameter-specific details beyond reinforcing the email parameter's role. 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 'Request a table at a restaurant' and distinguishes it from confirmed bookings. The sibling tool list includes 'create_booking', highlighting the difference: this is only a request, not a confirmed 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?

It explicitly says the restaurant is not notified yet, the request is held pending email confirmation, and the user must check their inbox. It further advises to use a real email and notes that the restaurant confirms out of band, providing clear when-to-use guidance.

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

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

With no annotations, the description fully discloses the temporary nature, no payment, expiry, and max limits. Clearly states the hold 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?

Front-loaded with key action, provides critical details in two sentences with no wasted words. All sentences add 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 output schema, the description explains the return value (checkout URL) and covers purpose, constraints, and alternatives, making it fully self-contained.

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

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

Schema coverage is 100%, so baseline 3. The description adds context about max limits (10 tickets, 10 types) and the return of a checkout URL, 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 tool holds tickets for events sold through Wix Events and returns a checkout URL. It specifies it's for site-sold events, distinguishing it from siblings like create_booking 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?

Explicitly states when to use (for events sold through this site) and when not to (use event's own ticketUrl for external events). Provides max limits (10 tickets, 10 types).

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 key behavioral traits: confirmation email with 24-hour expiry, RSVP only completes when recipient clicks link, link deliberately not returned to caller. This is exceptionally 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?

Description is front-loaded with purpose and key constraint ('free event'), then details process. Every sentence is meaningful, though some repetition (e.g., 'the confirmation link is deliberately not returned to you' could be combined with earlier statement). Still efficient for the amount of critical info.

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 fully explains expected outcome (confirmation email followed by user action). Covers all essential aspects: who receives email, timeline, what happens after clicking, and what the agent should tell the user. Sibling tools like 'reserve_event_tickets' might handle paid events, so this description is complete for its niche.

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. Description adds value by clarifying 'email' parameter: 'the confirmation link is sent here' and 'event_slug': 'from list_events'. FirstName and lastName not elaborated but schema descriptions suffice.

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)' with a specific verb and resource. Distinguishes from sibling 'reserve_event_tickets' by specifying 'free event', indicating it's for free events 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?

Explicitly tells when to use (RSVP to free events) and provides critical instructions: no one is on guest list, confirmation email sent, must use real address, link not returned. Also tells agent to inform user to check inbox.

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 (all restaurants, all menu items), grouping behavior, and return fields (price, description, dietary labels, place URL). This is sufficient for a read-only search tool, though no annotations are present.

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

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

Three concise sentences with no wasted words. The action is front-loaded, and each sentence adds distinct value: purpose, behavior, usage guidance. Perfectly sized.

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 no output schema and only two parameters, the description covers purpose, return content, parameter behavior, and usage context completely. Nothing 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?

Schema coverage is 100%, and the description adds meaning beyond schema: explains grouping behavior, the effect of omitting the query, and the nature of results. This enriches the schema's parameter 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 uses a specific verb ('Find') and resource ('which restaurants serve a dish'), clearly distinguishing it from sibling tools like get_restaurant_menus or search_places. The grouping by dish is unique and well-stated.

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 tells when to use this tool ('where can I eat X' questions) and provides guidance on omitting the query for top dishes. It implies not to use for single-restaurant menus, but does not explicitly list exclusions or 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?

With no annotations, the description fully carries the burden. It discloses accent-insensitive and typo-tolerant matching, relevance ranking, and structured opening hours format (day mapping, time HHMM). Missing behavior like pagination is implied by 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 sentences, no wasted words. Purpose is front-loaded. Essential details are packed efficiently.

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 explains the return format for opening hours and mentions relevance ranking. It does not detail full response structure (e.g., other fields), but the key behavioral aspects are covered.

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 significant value: explains accent-insensitive/typo-tolerant for q, case-insensitive substring match for category and neighborhood, and opening hours format. It goes beyond schema definitions.

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 like restaurants and cafes, with accent-insensitive and typo-tolerant matching. It distinguishes itself from siblings like get_place (specific place) and search_dishes (dishes).

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?

While the description explains the tool's behavior and optional filters, it does not explicitly guide when to use this tool over alternatives (e.g., get_place for known ID, search_dishes for dishes). No when-not-to-use guidance is 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. Mentions success return (submissionId) but does not disclose error conditions, idempotency, or authentication requirements. Adequate but could be more transparent.

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

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

Two brief sentences, each serving a clear purpose: stating the action and providing usage context. No filler or redundancy.

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

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

Covers purpose, prerequisites, and return value. Missing error scenarios or more detailed behavior, but sufficient for a simple form submission tool given 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?

Adds significant value beyond schema by explaining that fields are key-value pairs matching list_forms output and formId comes from list_forms. This practical guidance aids correct parameter construction.

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 submits a form on behalf of the user, specifies the platform (Wix Forms), and distinguishes from sibling list_forms by mentioning it 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 clear context for correct usage. Lacks explicit when-not or alternative tools, but the prerequisite guidance is strong.

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