Pinheiros

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

With no annotations, the description fully carries the burden. It discloses that the tool returns a checkout URL (not a confirmation), that booking stays off calendar until payment, that email is not verified, and that taken slots are rejected.

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?

Every sentence adds critical information. The structure is logical: purpose, critical caveat, user instruction, prerequisite, and behavioral note. 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?

The description fully covers the tool's behavior and prerequisites. Without an output schema, it explains the return value (checkout URL) and error condition (rejected taken slot). Minor gap: no details on response format or error codes, but sufficient for an 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%, so baseline is 3. The description adds value by specifying the source of required values (get_availability for dates, list_booking_services for serviceId) and emphasizing the contact object's necessity.

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-resource pair ('Book an appointment slot at a venue') and clarifies that the tool is part of Wix Bookings. It distinguishes itself from siblings like get_availability by stating its purpose and preconditions.

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: call get_availability immediately before, informs that nothing is booked until payment, and instructs the user to open the checkout URL. No ambiguity about when to use.

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

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

With no annotations provided, the description carries the full burden. It mentions the URL creation and no login requirement but omits details like error behavior, URL expiration, or side effects of creation.

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. The main action is front-loaded and each sentence provides essential information.

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

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

Given the simple structure (1 param, no output schema), the description covers the core functionality well. However, it lacks specification of the return value (the URL itself) which would aid 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% (only one parameter, items). The description adds context (URL, no login) but does not significantly enrich the meaning of the items parameter beyond what the schema already describes.

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 Wix Stores products, using specific verbs ('Create') and resource ('direct checkout URL'). It distinguishes the tool from siblings like list_products by focusing on payment completion.

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 completing payment via a URL and notes that no login is required, but it does not explicitly state when to use versus alternatives or provide 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?

No annotations provided, so description carries full burden. Discloses time zone behavior but does not explicitly state that the tool is read-only or idempotent. 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?

Very concise (2 sentences) with no unnecessary words. Information is front-loaded: the tool's purpose and key parameters are immediately clear.

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

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

Given no output schema, description does not explain what the response looks like (e.g., list of time slots, any pagination). Lacks details on returned data format, which would help an agent use the result.

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 meaning beyond the schema: explains that serviceId comes from list_booking_services, date must be YYYY-MM-DD, and place_slug must match the one used in list_booking_services. Also adds context about time zones for the slot times.

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 available time slots for a bookable service on a given date (Wix Bookings).' It uses a specific verb and resource, distinguishing it from sibling tools like 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 guidance: pass serviceId from list_booking_services, date format YYYY-MM-DD, and same place_slug. Also warns about time zone differences. Does not state when not to use or mention alternatives like create_booking.

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

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

No annotations are provided, so the description carries full burden. It describes the tool as retrieving ticket information (names, prices, sale status, how many left), implying a read-only operation. However, it doesn't explicitly state read-only or mention auth requirements or rate limits. The output description adds 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?

Two sentences, both informative and front-loaded. The first sentence states purpose and context, the second gives input and output. 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?

Despite no output schema, the description summarizes what is returned. It fits well with sibling tools: list_events provides slugs, get_event_tickets provides details, reserve_event_tickets takes action. The description is sufficient for an agent to understand how to use the tool in context.

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

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

The schema describes event_slug with 'Event slug from list_events.' The description reinforces this and explains where to obtain the slug, adding context beyond the schema. With 100% schema coverage, the baseline is 3, but the description adds value by clarifying the source.

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 'ticket types and prices', and the context 'Wix Events'. It specifies the input (event slug from list_events) and output (ticket names, prices, sale status, amount left). This differentiates it from sibling tools like reserve_event_tickets and rsvp_event.

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

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

The description explicitly instructs to pass the event slug from list_events, providing a clear dependency. It implies usage before reserving tickets, but does not explicitly state when not to use it or mention alternatives. The guidance is helpful but not exhaustive.

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?

Discloses what is returned, but lacks details on authentication requirements, error states (e.g., no loyalty program), or side effects. With no annotations, the description should provide more 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?

Single sentence, efficient, front-loaded with key information. 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 zero parameters and no output schema, the description sufficiently covers the tool's purpose and output. Could note if the loyalty program must be configured, but overall 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?

No parameters exist; schema coverage is 100% trivially. Description adds no parameter info, but none is needed. 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?

Clearly states it retrieves loyalty program details for the site, specifying exact return fields (program name, points currency, tier structure). No ambiguity and distinct from all 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 as a standard info getter, but no explicit when-to-use or when-not-to-use guidance. Could mention it's for sites with Wix Loyalty enabled, but not critical.

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 does not explicitly state that the operation is read-only or non-destructive, nor does it disclose any side effects, auth requirements, or limits. The description only lists returned fields, missing behavioral context.

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

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

The description is a single sentence that efficiently conveys the purpose and key return fields. It is front-loaded with the core action, though the enumeration of many fields makes it slightly dense. 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?

Given the complexity (single parameter, no output schema), the description lists all major return fields (opening hours, open_now, attributes, delivery, ratings, address, neighborhood). It is complete enough for an agent to understand the tool's output, though the dense list could be structured better.

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

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

The schema has 100% coverage with a single 'slug' parameter described as 'URL slug of the place'. The description echoes this with 'by its URL slug', adding no new semantics beyond confirming usage. 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 verb 'Get full details' and specifies the resource 'place by its URL slug'. It enumerates specific returned fields (opening hours, open_now, attributes, delivery, ratings, address, neighborhood), distinguishing it from sibling tools like get_reviews or 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?

The description implies use for retrieving details of a specific place via slug, but does not explicitly state when to use this tool versus alternatives like search_places or get_reviews. No exclusions or conditional 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 the description fully discloses the read-only nature by describing the returned data (menus, sections, dishes, prices, dietary labels). It implies no side effects, which is adequate for a query 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?

Three sentences, each earning its place: purpose, return details, prerequisite 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?

With only one required parameter and no output schema, the description fully covers what the tool does, what it returns, and how to get the input. 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?

Schema description already covers the place_slug parameter (100% coverage). Description adds value by explaining how to obtain the slug via search_places or list_categories, providing useful context 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 verb 'Get' and the resource 'food menu for a specific restaurant', and distinguishes it from siblings like search_dishes by specifying it returns sections, dishes, descriptions, prices, and dietary labels.

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 advises using search_places or list_categories first to obtain the required place_slug, providing clear context for when to use this tool. No when-not-to-use guidance is needed given the single parameter.

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 the returned fields adequately but does not mention default behavior (e.g., ordering), pagination, or authentication requirements. For a simple read tool, this is acceptable but could be improved.

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 filler. First sentence clearly states purpose, second adds return details. 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 low complexity (1 optional param, no output schema), description covers essential return fields and purpose. Minor gap: no mention of empty results behavior, but overall 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% via the 'limit' parameter description. The tool description adds no additional semantic meaning beyond the schema, so 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?

Description clearly states the tool gets published reviews and lists specific return fields (reviewer name, rating, title, content). It distinguishes itself from sibling tools like get_site_info or list_products by focusing on reviews for 'this site' with explicit mention of Wix 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?

Description implies reading reviews but provides no explicit guidance on when to use this tool versus alternatives like list_products or list_blog_posts. No when-not-to or alternative suggestions are given, leaving usage inference to the agent.

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

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

No annotations are provided, so the description carries the full burden. It discloses return content and a prerequisite, but does not mention idempotency, authorization details beyond the prerequisite, error handling, or absence of 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?

The description is two sentences, front-loaded with purpose and return content, with no extraneous information.

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

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

For a two-parameter tool with no output schema, the description covers purpose, return fields, and a prerequisite. It is mostly complete but could detail the return structure more explicitly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds context (e.g., 'movie slug from list_movies') but largely reiterates schema information, adding marginal 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 gets showtimes for a specific movie at cinemas in the neighborhood for a given date, distinguishing it from sibling tools like list_movies (which lists movies) and get_availability (which likely covers different 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 notes a prerequisite (movies_enabled on the site) but does not explicitly state when to use this tool over alternatives or when not to use it. The guidance is implied but not explicit.

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 that the tool returns dynamic data (local time and weather), implying a read-only, non-destructive operation. No side effects, rate limits, or auth needs are mentioned, but for a simple getter this is adequate.

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

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

The description is two sentences with no wasted words. The first sentence clearly enumerates the output fields, and the second provides direct usage context. 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 has no parameters, no output schema, and no annotations, the description covers all necessary information: what the tool does, what it returns, and when to use it. The complexity is low, and the description fully satisfies the agent's needs.

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

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

There are zero parameters, so the schema provides no meaningful information. The description adds value by listing the specific fields returned (name, locale, domain, description, canonical URLs, local time, current weather), which helps the agent understand what the tool provides without needing to see an output 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 specifies exactly what the tool returns: name, locale, domain, description, canonical URLs, local time, and current weather. The verb 'Returns' clearly indicates a read operation, and the resource 'site info' is well defined. It distinguishes itself from sibling tools by highlighting unique features like local time and weather.

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 use cases: 'for any "what time is it there" or "what's the weather like" context.' This provides clear guidance on when to invoke the tool. While it does not mention when not to use it or alternatives, the tool is distinct enough that no exclusions are necessary.

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 bears full responsibility. It indicates a read operation but does not disclose ordering, pagination, authentication requirements, or any side effects. Only 'recent published' scope is noted.

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?

A single sentence that front-loads the main purpose and is free of redundant information. Every part is essential.

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

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

For a simple list tool with two optional parameters and no output schema, the description is mostly complete. It specifies return fields and scope, but lacks mention of default ordering (e.g., by date). Minor gaps.

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

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

Schema coverage is 100% (both parameters have descriptions). The description adds no extra meaning beyond the schema; it does not explain parameter behavior or provide examples.

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 'List recent published blog posts for this site (Wix Blog)' with a specific verb and resource, and lists returned fields, distinguishing it from sibling tools like list_events or list_faqs.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of when not to use it or comparison to other list 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?

Fully discloses behavior: dual mode based on place_slug, that it returns all services even if not bookable, with null id when bookableViaMcp is false. No annotations to contradict, so description carries full burden and meets it.

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 verbose but well-structured: first sentence gives main purpose, then details. All sentences add value; no redundancy, but could be slightly more 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?

Given simple tool with one optional parameter, no output schema, and no annotations, description covers behavior, return fields, and edge cases (non-bookable services). Also provides error handling guidance.

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 description for place_slug. Description adds value by noting source (search_places), strong recommendation, and behavioral consequence of omission, enhancing understanding 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 a venue's services with price and duration, and distinguishes between using place_slug (venue services) vs. omitting (directory's own services). This differentiates it from siblings like list_products 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?

Gives explicit guidance: pass place_slug in most cases, omitting yields directory services rarely, and only venue services work with create_booking. Also advises checking bookableViaMcp and falling back to bookingUrl.

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 what the tool returns (category taxonomy details), but does not mention any behavioral aspects like caching, cost, rate limits, or potential for large responses. For a read-only list tool, this is adequate but lacks transparency on performance.

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 no wasted words. Front-loads the main purpose. Every part adds value: lists what the output contains (groups, subcategories, labels, types, counts). Extremely concise for the information conveyed.

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 covers the essential purpose and output content. However, it does not specify the structure of the return (e.g., JSON array of objects with fields), which could help an agent parse the output. Slightly incomplete for a tool with no schema.

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

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

There are no parameters, and schema coverage is trivially 100%. The description adds value by detailing the output components beyond what the schema provides (which is empty). Baseline for 0 params is 4, and the description earns it by clarifying the return structure.

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

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

Description clearly states it returns the full category taxonomy with specific components: top-level groups, subcategories, localized labels, schema.org types, and live place counts. The verb 'returns' and resource 'category taxonomy' are precise, and it distinguishes itself 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 explicit when-to-use or when-not-to-use guidance. The description implies it returns the complete taxonomy, but it doesn't compare with alternatives or mention prerequisites. For a parameterless tool, minimal guidance is acceptable, but a brief usage hint (e.g., 'Use this to get the full category hierarchy') would improve it.

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

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

With no annotations, the description fully carries behavioral disclosure. It details that events within 7 days include a weatherForecast, and that the 'agora' filter is resolved live without caching. No destructive actions are implied.

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 with two sentences. The first sentence front-loads the core purpose, while the second provides additional detail. It could be slightly restructured for clarity, but remains 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, the description adequately specifies return fields and conditional weather data. It omits error handling or authentication info, but for a read-only listing 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?

Schema coverage is 100%, yet the description adds value by explaining the 'agora' filter's semantic nuance (excludes season runs) and default/max limits. This goes beyond the 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 lists upcoming events with specific fields (date, venue, price, URL) and mentions special behavior for events within 7 days. It does not explicitly differentiate from sibling tools like list_movies or list_blog_posts, but the resource is distinct.

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 usage context, including when to use the 'filter' parameter (e.g., 'agora' for live events) and how to leverage the weather forecast. However, it does not explicitly state when not to use this tool versus 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?

Annotations are absent, and the description only states it retrieves grouped FAQs. No details on pagination, rate limits, or data freshness are provided, though the tool is read-only.

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-load the core action and usage. No superfluous 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 zero parameters and no output schema, the description adequately covers purpose and usage context. Grouping by category is mentioned, which adds value.

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 exist, and schema coverage is 100%. Base score for 0 params is 4.

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

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

The description clearly states the tool retrieves all FAQ questions and answers grouped by category. The verb 'get' and resource 'FAQ' are specific. No sibling tool directly conflicts, so differentiation is implicit.

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 to use this tool for answering common site questions like hours, parking, policies. No alternative tool for FAQs exists, so when-not is not needed.

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

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

With no annotations, the description carries full behavioral disclosure. It accurately describes the read-only nature of listing forms and specifies return data. While it could explicitly state it's a read operation, the behavior is clear from context and no contradictions exist.

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

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

The description is extremely concise—two sentences that front-load the purpose and provide clear guidance. Every sentence earns its place with no extraneous information.

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

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

Given the tool's simplicity (no parameters, no output schema, low complexity), the description fully covers all necessary context: what it does, what it returns, and when to use it relative to sibling tools.

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 no parameters, so schema coverage is 100% by default. The description adds value by indicating that the response includes field definitions, which goes beyond the empty schema. Baseline for 0 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 lists available contact/signup forms on the site, specifies the resource (Wix Forms), and outlines return values (name, ID, field definitions). It distinguishes itself from the sibling submit_form by explicitly mentioning its use before that tool.

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 this tool before submit_form to discover fields, providing clear usage context. It does not include explicit when-not-to-use scenarios, but the guidance is sufficient for a simple list 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 carries full burden. It describes the output as ranked places with editorial notes, which implies a read-only operation, but it does not explicitly confirm no side effects, authentication needs, or rate limits. The name 'list_guides' and verb 'List' strongly suggest safety, but more explicit disclosure would improve 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 two sentences with no wasted words. The action ('List curated editorial guides') is front-loaded, and the use case sentence adds value. 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?

For a simple list tool with one parameter and no output schema, the description adequately conveys the type of data returned (guides with ranked places and editorial notes). However, it lacks details on the structure of each guide, pagination (only limit, no offset), and whether ordering is fixed. Without output schema, more context on the return format 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?

Schema coverage is 100% for the single parameter 'limit', with adequate schema description ('Max guides to return (default 20, max 50).'). The tool description does not add additional parameter meaning beyond the schema, which is acceptable given the coverage.

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

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

The description clearly states it lists curated editorial guides ('best of' lists) with ranked places and editorial notes, and provides a specific use case ('best X in this neighborhood' questions). This distinguishes it from sibling tools like list_blog_posts or 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?

The description implicitly guides when to use (for curated 'best of' lists and neighborhood questions) but does not explicitly state when not to use or mention alternatives. It 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?

No annotations provided; description carries full burden. Discloses return content and filtering capabilities but missing details on error handling, pagination, 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?

Two concise sentences; no redundant information. Front-loaded with purpose and condition.

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, filtering, and output fields adequately for a read-only list tool with no required parameters. No output schema, but description explains return fields.

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

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

Schema already covers 100% of parameters with descriptions; description adds specific meaning for status enum values (e.g., 'now_showing' defined as films with upcoming showtimes).

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 listing movies available in a neighborhood, specifies categories (now-showing, coming-soon, streaming) and included fields. Does not explicitly distinguish from sibling tools but is self-explanatory.

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. Mentions a prerequisite ('only on sites with movies_enabled') but lacks context for tool selection.

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 return fields and the special behavior of FLASH offers (countdown deadline), but does not mention pagination, ordering, or that it is read-only. The purpose is clear but additional behavioral traits are implicit.

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 concise sentences with no fluff. It front-loads the purpose, lists returned fields, and adds a key detail about FLASH offers. 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 explains return values. For a list tool with only two optional parameters, it covers essential context. It does not mention ordering or default limit but the schema covers that. Sibling differentiation is present, making it contextually complete for an 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%, so baseline is 3. The description mentions FLASH offers which relates to the 'kind' parameter, but adds no new information beyond the schema's own description. The 'limit' parameter is not referenced in the 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 lists active promotions and deals, specifying its output fields (discount label, promo code, CTA link, validity window, business). It distinguishes itself from sibling tools like list_products or list_pricing_plans by focusing on time-limited promotions, including explicit mention of FLASH 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 no guidance on when to use this tool versus alternatives like get_loyalty_info or list_pricing_plans. It does not include exclusionary context or typical use cases, leaving the agent to infer suitability.

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, but the description lists return fields (name, description, price, etc.) and implies a read operation with no side effects. Could explicitly state idempotence, but sufficient for a list 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: first introduces tool and key parameter, second explains usage and return contents. No redundancy, front-loaded, 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?

Completeness is good given single optional parameter and no output schema. Explains both modes, what is returned, and dependency. Minor gap: no mention of pagination or sorting, but likely unnecessary for pricing lists.

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

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

Schema already describes place_slug; description adds context: strongly recommended, explains behavior difference, and links to search_places. Adds value beyond schema, but schema coverage is 100% so baseline 3, elevated due to extra guidance.

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/subscription plans, distinguishes between venue-specific and site-wide plans using place_slug, and the verb-resource combination is precise. It differentiates from sibling list tools by specifying 'pricing plans' and the venue context.

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 advises to use place_slug from search_places for venue plans ('what you want in almost every case'), and warns that omitting it gives directory plans. Provides clear when-to-use and dependency 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 are present, so the description must bear the full burden. It implies a read-only operation ('List'), but does not explicitly state that the tool is non-destructive, does not describe pagination behavior beyond the limit parameter, and omits details on authentication requirements or error handling. The description is adequate but not thorough.

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

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

The description is a single, front-loaded sentence that conveys the core purpose and return fields. It is very concise, though it could potentially include more structured details without losing conciseness.

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 simplicity of the tool (2 optional params, no output schema, no annotations), the description minimally covers the functionality. However, it lacks guidance on default behavior, error states, and how it fits among many sibling list_* tools, leaving gaps for an agent to fully understand usage.

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

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

Schema description coverage is 100%, so the input schema already documents both parameters (q and limit). The description adds no extra meaning about parameter usage beyond what the schema provides, meeting the baseline but not exceeding it.

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

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

The description clearly states the verb 'List', the resource 'products', and specifies the context 'in this site's store (Wix Stores)'. It also enumerates the returned fields (name, price, stock status, product type), making the tool's purpose distinct 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, filtering strategies, or when to prefer other list_* tools from the sibling list.

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

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

The description mentions what is returned (name, profile URL, category, metadata) but does not discuss pagination behavior (though limit parameter implies it), authentication requirements, or other side effects. With no annotations, the description carries the full burden and is moderately 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 two sentences, front-loaded with the core purpose, provides examples, and includes return information. Every sentence adds value with 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?

For a simple list tool with one parameter and no output schema, the description adequately explains the resource and return fields. It could mention default limit or sorting, but the schema covers the limit default. Overall, it is sufficiently complete for an agent to understand the tool's behavior.

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 single parameter 'limit' is fully described in the schema (100% coverage). The description does not add additional information about the parameter, so 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 that the tool lists solo service-provider profiles (businesses without fixed physical location), provides examples (dog walkers, tutors), and distinguishes it from sibling tools like list_booking_services which likely list different entities.

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 defines the scope (solo service-providers without physical location) but does not explicitly state when to use or avoid this tool relative to alternatives like list_booking_services or list_categories.

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 fully describes behavioral traits: the restaurant is not notified until confirmation, the link expires in 24 hours, and the confirmation link is not returned to the agent. This goes beyond basic purpose and provides critical operational details.

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

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

The description is concise and front-loaded with the purpose. Every sentence provides valuable information without repetition. The warnings and instructions are clear and necessary.

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

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

Given the tool's complexity (7 parameters, no output schema), the description covers the essential workflow and caveats. It could be improved by explaining what happens on failure or when the link expires, but overall it provides sufficient context for correct usage.

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

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

Schema coverage is 100%, providing good baseline. The description adds meaningful context for the 'email' parameter, explaining it must be a real address and that the confirmation link is sent there. This enhances understanding beyond the schema's description.

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

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

The description clearly states the tool's purpose: to request a table at a restaurant. It distinguishes this from a confirmed booking by emphasizing the email confirmation step and that the restaurant is not notified immediately. This sets it apart from sibling tools like 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?

The description provides explicit usage guidelines, including telling the user to check their inbox, using a real email, and noting that the request is not a confirmed booking. However, it does not explicitly mention when to use this tool versus alternatives like create_booking, though the context implies the difference.

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?

Since no annotations are provided, the description fully carries the burden. It discloses key behavioral traits: the hold is temporary, no payment occurs, it expires automatically, and there are maximum limits (10 tickets, 10 types). This sufficiently informs the agent of consequences.

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 with two sentences. It front-loads the main action and follows with critical caveats (temporary, expiration, limits, alternative). Every sentence adds value; 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 the tool's moderate complexity, the description covers purpose, usage constraints, alternatives, and return value (checkout URL). With full schema coverage and no output schema needed, the description is complete and sufficient for correct invocation.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides for the two parameters ('event_slug' and 'tickets'). It does reinforce the purpose but doesn't enrich semantics.

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

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

The description clearly states the tool's action ('Hold tickets'), the resource ('event sold through this site'), and the outcome ('return a checkout URL'). It also distinguishes itself from siblings by specifying it only works for Wix Events, not external platforms.

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 (for events sold through this site) and when not to use (for events sold elsewhere, with a specific alternative: use the event's own ticketUrl). This provides clear guidance for selection.

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 key behaviors: the RSVP is not immediate, a confirmation email is sent with a 24-hour expiry link, and the link is deliberately not returned to the agent. This is thorough 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 wasted words. The purpose is front-loaded, and critical flow details are compactly presented. 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 4 required parameters, no output schema, and no annotations, the description explains the core workflow and caveats. It lacks return value information, but the focus on the confirmation process is sufficient for the tool's purpose.

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 for 'email' (the guest's own email for confirmation) and 'event_slug' (from list_events). These details enhance understanding beyond the 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 clearly states the tool RSVPs to a free event on Wix Events and describes the unique email confirmation process. It distinguishes itself from siblings like 'reserve_event_tickets' by specifying the free event nature and the confirmation flow.

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

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

Provides clear guidance on using a real email address and notifying the user to check their inbox. Implicitly sets usage context (free events via email confirmation), but does not explicitly exclude other scenarios or name 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?

Describes return structure (grouped by dish with price, description, labels, URL) and behavior when query is omitted. No annotations, so description carries burden; it's sufficiently transparent without mentioning auth or limits.

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

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

Two sentences, front-loaded with purpose, zero waste. 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?

For a simple 2-parameter tool with no output schema, the description fully explains behavior and return format. 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?

Schema coverage is 100%, but description adds useful context: default/max for limit, and that omitting query lists top dishes. Example clarifies 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?

Clearly states the tool finds which restaurants serve a dish, with a concrete example ('feijoada') and description of grouping. Distinct from siblings like search_places or get_restaurant_menus.

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 this for any "where can I eat X" question.' Also explains omitting query for top dishes. Missing explicit when-not-to-use or alternatives, but guidance 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?

With no annotations, the description carries full burden. It discloses key behaviors: accent-insensitive and typo-tolerant matching, AND logic for attributes, precomputed open_now boolean, and result fields (delivery links, rating, hours). 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 a single paragraph with no wasted words. Each sentence adds value: purpose, matching behavior, filter explanation, result structure, and common slugs. Information-dense yet easy to parse.

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

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

Given 6 parameters and no output schema, the description covers all key aspects: matching algorithm, filter behavior, result fields (open_now, attributes, delivery, rating, hours), and amenity slugs. It provides sufficient context 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%, and the description adds significant meaning: q matching details, open_now 'at this exact moment', attributes 'ALL must match', and result fields like delivery platform names and hours format. This greatly enriches the 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 'Search for places (restaurants, cafes, shops, etc.)' with a specific verb and resource, and includes examples of place types. This distinguishes it from siblings like 'search_dishes' which focuses on 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?

The description explains the tool's purpose and filter capabilities (category, neighborhood, open_now, attributes), implying when to use it for place searches. However, it does not explicitly state when not to use it or provide direct alternatives, though sibling tool names offer context.

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

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

No annotations provided, so description carries full burden. It mentions submission on behalf of user and returns submissionId, but lacks details on side effects, permissions, or error conditions. 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 sentences, no filler. Essential information is front-loaded: action, prerequisite, return value. 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 2 required params, high schema coverage, and no output schema, the description covers the necessary steps (prerequisite, return) and is complete for the tool's simplicity.

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%, and parameter descriptions are clear. The description adds usage context (e.g., use list_forms to get keys) but does not significantly enhance meaning beyond schema. Baseline 3 is appropriate.

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

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

The description clearly states the action ('Submit a form'), the resource ('Wix Forms'), and the prerequisite step. It distinguishes from siblings like list_forms by indicating it is the next step after obtaining form data.

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 usage context. Does not explicitly list alternatives or when not to use, but the guidance is sufficient.

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