Interlagos

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

No annotations provided, so description carries full burden. It fully discloses the asynchronous payment requirement, that the slot is re-validated server-side, and that contact email is not verified until checkout. Excellent transparency.

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

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

Description is front-loaded with the main action and key caveats. While slightly long, every sentence adds necessary detail for correct tool usage.

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 complex async flow and absence of output schema, the description fully explains the expected outcome (checkout URL) and required user action. No gaps remain.

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

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

Schema description coverage is 100%, with all parameters documented. The description adds value beyond schema (e.g., startDate/endDate must match get_availability output, contact fields required by venue). Nested objects are explained.

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

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

The description states the tool books an appointment slot at a venue (Wix Bookings) and clarifies that nothing is booked until payment is completed via a checkout URL. This clearly distinguishes it from siblings like get_availability or create_checkout.

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

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

Explicitly instructs to call get_availability immediately before and explains the payment flow (checkout URL, user must open link). Does not explicitly state when not to use, 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 carries the burden. It explains the user flow (completes payment on site) and authorization hint (no login needed), but lacks details on side effects, rate limits, or error conditions.

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

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

The description is highly concise with two sentences that front-load the purpose and key behavior, containing no redundant or 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 single parameter and no output schema, the description is largely complete. It could improve by noting the URL's temporary nature or potential errors, but overall adequately covers the tool's function.

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

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

The input schema has 100% coverage for the one parameter, so the description adds no extra meaning beyond what the schema already provides (defaults, required fields).

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

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

The description clearly states the specific action ('create a direct checkout URL'), the resource ('store products from Wix Stores'), and the unique value ('no login required'), distinguishing it from sibling tools like list_products.

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

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

The description implies usage after listing products, but does not explicitly state when to use vs alternatives, nor does it provide exclusions or prerequisites for use.

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

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

No annotations are provided, so the description carries the burden. It discloses a key behavioral trait: slot times are returned in the venue's timezone, not the directory's. This is valuable context beyond basic functionality.

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 zero waste. The first sentence states the purpose, the second provides critical usage details. Every word earns its place.

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

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

No output schema, and the description does not explain the return format or error behavior. For a simple slots retrieval tool, this is adequate but not complete. Missing details like whether it returns an empty list for no availability.

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 meaning: it explains the relationship between serviceId and list_booking_services, the date format, and the importance of using the same place_slug. This 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 clearly states the verb 'Get', the resource 'available time slots for a bookable service on a given date', and specifies it's for Wix Bookings. It distinguishes from siblings like list_booking_services (which lists services) and create_booking (which books).

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 when to use and provides clear instructions: pass serviceId from list_booking_services, use same place_slug, and warns about timezone. It does not explicitly state when not to use, but the context makes it obvious.

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 return values (ticket names, prices, sale status, remaining count) and implies read-only via 'get'. Does not mention error conditions or rate limits, but adequate for a simple query.

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, no wasted words. Efficiently conveys 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?

No output schema, but description explains return values. Tool is simple (one parameter, no nested objects), and description fully covers usage and output. No gaps identified.

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

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

Schema covers 100% of parameter 'event_slug' with description 'Event slug from list_events.' Description echoes this, adding no new semantic information beyond the schema.

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

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

Description clearly states it gets ticket types and prices for a specific event, specifying the resource and action. It lists return fields (ticket names, prices, sale status, how many left), distinguishing it from siblings like reserve_event_tickets.

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

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

Explicitly instructs to pass the event slug from list_events, providing a usage chain. Lacks explicit when-not-to-use or alternative tools, but context is clear for the simple single-parameter 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 present, so the description must fully convey behavioral traits. It only describes the output, with no mention of side effects, safety (e.g., read-only nature), authentication requirements, or rate limits. The name suggests a read operation, but the description does not explicitly confirm safety.

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

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

The description is brief, consisting of two sentences that deliver the key information without redundancy. It is front-loaded with the primary action and then details the return 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 lacking an output schema, the description adequately specifies the return content (program name, points currency, tier structure). It does not mention potential edge cases or completeness of data, but for a simple info tool it provides sufficient 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?

There are no parameters, so schema coverage is 100% (empty). The description adds no parameter-specific meaning beyond the schema, which is appropriate for zero parameters. 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 tool retrieves loyalty/rewards program details for the site, naming specific return fields: program name, points currency name, and tier structure. This provides a precise verb+resource description that distinguishes it from sibling tools like get_place or get_site_info.

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

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

The description explains what the tool does but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternative siblings. Usage context is implied but no exclusions or comparisons are given.

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

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

No annotations are provided, so the description carries full burden. It lists returned fields but does not disclose behavioral traits such as error handling, rate limits, authorization requirements, or what happens with invalid slugs.

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

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

The description is two sentences with no wasted words. It front-loads the purpose and then lists key return fields. Structure is clear 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?

Given the single parameter and no output schema, the description compensates by enumerating return fields (opening hours, open_now, attributes, delivery, etc.). It lacks edge-case or error information but is otherwise thorough for a simple get-detail tool.

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

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

Schema description coverage is 100% for the single parameter 'slug'. The description adds 'by its URL slug' which is consistent with the schema's 'URL slug of the place', but does not provide significant additional meaning beyond the schema.

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

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

The description clearly states the verb 'Get', the resource 'full details for a specific place', and the mechanism 'by its URL slug'. It lists specific data fields returned, distinguishing it from sibling tools 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?

The description implies usage for fetching details of a single place but does not explicitly state when to use this versus alternatives like search_places. No when-not or alternative tool 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. It describes the return content comprehensively (menus, sections, dishes, etc.). While it doesn't explicitly state read-only behavior, it is implied by 'Get' and listing returns. Minor gap: no mention of error handling or rate limits, but overall 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: first states purpose and output, second provides prerequisite guidance. No wasted words, efficiently structured.

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

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

No output schema, but description comprehensively lists return contents. Provides prerequisite knowledge (how to get place_slug) relevant to sibling context. Covers all essential aspects for a simple one-param 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?

Only one parameter with high schema coverage (100%). The description adds value beyond the schema by explaining the source of place_slug (search_places or list_categories) and giving an example format, aiding agent understanding.

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

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

The description clearly states the verb 'Get' and resource 'food menu', and specifies what is returned (sections, dishes, descriptions, prices, dietary labels). This distinguishes it from sibling tools like search_dishes or get_place.

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

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

Explicitly instructs to use search_places or list_categories first to obtain the required place_slug, providing clear precondition and alternative tools. This guides the agent on when and how 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 disclose behavioral traits. It only states what is returned but lacks details on side effects, authentication requirements, rate limits, or edge cases like empty results.

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 concise sentences with no fluff. The first sentence states the purpose, the second lists return fields. Every word earns its place.

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

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

For a simple tool with one optional parameter and no output schema, the description sufficiently explains the tool's purpose and output fields. It omits potential details like pagination or ordering, but these are not critical for basic usage.

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

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

Schema coverage is 100% (the single 'limit' parameter is described in the schema). The description adds no additional parameter information beyond the schema, but since coverage is high, 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 tool retrieves published reviews and lists the returned fields (reviewer name, rating, title, content). It distinguishes from sibling list tools by specifying the resource type, but does not explicitly differentiate from other 'get' 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?

No guidance is provided on when to use this tool versus alternatives, nor are there any prerequisites or exclusions mentioned. The description assumes the agent knows the 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 exist, so the description must fully disclose behavior. It correctly indicates the tool returns dynamic data (local time and weather). However, it does not mention caching behavior, authentication requirements, or any side effects. The description is adequate but lacks depth.

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 filler. It front-loads the main purpose and adds specific examples, making every word earn its place.

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

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

Given no parameters and no output schema, the description thoroughly covers what the tool returns, including examples of data (time, weather). It is complete for this simple tool.

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

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

The input schema has zero parameters, so the description need not add parameter information. Baseline score of 4 applies, and the description provides no redundant parameter info.

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 'Returns' and the resource 'basic information about this neighborhood directory' including specific data like local time and weather. It distinctly differentiates from sibling tools which focus on bookings, events, or listings.

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 provides usage context: 'Use this for any "what time is it there" or "what's the weather like" context.' It could be improved by stating when not to use it, but the given guidance is clear and sufficient.

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

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

No annotations are provided, so the description must convey behavioral traits. It states the tool returns specific fields and implies it only returns published posts, but omits details like sorting order, empty results behavior, or pagination. This 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 sentence of 16 words that immediately conveys the tool's purpose and output. Every word adds value, and no extraneous information is present.

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

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

For a simple list tool with two optional parameters and no output schema, the description covers the main purpose and output fields. It does not mention default ordering or pagination behavior, but given the tool's simplicity, this is mostly complete.

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

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

Schema coverage is 100% with both 'limit' and 'category' described in the input schema. The description does not add any additional parameter semantics beyond what the schema already provides, 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 the verb 'List' and the resource 'recent published blog posts for this site (Wix Blog)', and lists the fields returned. It is distinct from sibling tools that handle other entities like products, events, or bookings.

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

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

The description provides clear context that this tool is for listing published blog posts, but does not explicitly state when to use it versus alternatives or mention exclusions. Since no similar blog-related tool exists among siblings, this is sufficient.

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

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

Discloses that services are returned for all venues regardless of booking system availability, explains the bookableViaMcp flag, and notes that id is null when not bookable. This covers all behavioral nuances beyond the basic listing.

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?

While detailed, every sentence is necessary and well-ordered: purpose, parameter usage, return fields, edge case handling. Not verbose; efficient for the complexity.

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 fully explains return values (name, description, price, duration, bookableViaMcp) and the non-bookable scenario. No gaps for the tool's scope.

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 context to the sole parameter: where to get it (search_places), its effect (venue vs. directory services), and that it's strongly recommended. This goes well beyond the schema description.

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

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

Clearly states the tool lists a venue's services with price and duration. Distinguishes between listing for a specific venue vs. the directory's own services, which differentiates it from sibling tools like get_availability or create_booking.

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

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

Explicitly instructs to pass place_slug from search_places for almost all cases, and explains when to omit it. Provides guidance on handling non-bookable services via bookableViaMcp and 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?

The description indicates a read-only operation ('Returns...'), but with no annotations, it does not mention performance characteristics like response size or pagination. However, the lack of side effects 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?

The description is a single concise sentence that immediately states the tool's purpose and lists the returned 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 no parameters and no output schema, the description provides sufficient detail about the returned taxonomy (hierarchy, labels, types, counts). It is complete for an agent to understand what the tool does.

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

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

There are no parameters, so the schema coverage is 100%. Per guidelines, this yields a baseline of 4. The description does not need to add parameter semantics.

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

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

The description clearly states the tool returns the full category taxonomy with specific details (top-level groups, subcategories, localized labels, schema.org types, live place counts). It is distinct from sibling list tools that return 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 does not provide explicit guidance on when to use this tool versus alternatives. It is implied that it is for retrieving the category structure, but no context or exclusions are given.

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

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

Discloses behavioral traits beyond the input schema: events within 7 days include a weatherForecast, and the 'agora' filter is resolved live each call. No destructive behavior is indicated, which is appropriate for a read-only listing tool. Without annotations, description carries full burden and does so well.

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 the primary purpose stated first, followed by additional details about weather and filter. Every sentence adds value; no waste. The structure is logical 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 output schema, the description specifies returned fields (date, venue, price, URL) and the weather condition for upcoming events. It explains the filter parameter in detail. It does not mention pagination or default ordering, but for a simple list tool, it is sufficiently complete.

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

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

Schema coverage is 100%, so baseline is 3. The description adds significant value for the 'filter' parameter by explaining each enum option, especially 'agora' with its caching behavior. The other parameters (limit, upcoming_only) are adequately covered by the schema, so overall exceeds baseline.

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). The verb 'list' and resource 'events' are explicit. However, it does not explicitly differentiate from sibling tools like get_event_tickets or reserve_event_tickets, though the scope 'in this neighborhood' provides some distinction.

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 the 'filter' parameter to narrow results, especially explaining the 'agora' filter's live resolution advantage over cached pages. However, it does not specify when to use alternatives (e.g., get_event_tickets) or 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 provided, so description carries full burden. It states 'Get all' which implies a read operation, and mentions grouping. However, it does not disclose details like whether the result is paginated, limit, or structure of the response.

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. Front-loaded with the action 'Get all FAQ questions and answers'. Followed by grouping info and usage guidance.

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

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

For a simple read tool with no parameters and no output schema, the description covers the essential: what it returns and when to use it. Could have hinted at the return format (e.g., list with question, answer, category), but overall 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, so baseline is 4. The description adds meaning beyond the empty schema by explaining the tool's output (FAQs grouped by category) and typical use cases.

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

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

Clearly states it gets all FAQ questions and answers for the site, grouped by category. Distinguishes from sibling tools like list_blog_posts by specifying 'FAQ' and providing example uses (opening hours, parking).

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 this tool to answer common questions about the site, with concrete examples. Lacks explicit when-not-to-use, but context implies it's for simple FAQ lookups, not specialized queries.

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 correctly describes a read-only listing operation with no side effects, and mentions the return structure. It is transparent about what the tool does.

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 redundant information. The first sentence states the purpose and output; the second gives usage context. 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?

For a simple tool with no parameters and no output schema, the description adequately explains what it does, what it returns, and how it fits into a workflow (with submit_form). Slightly more detail on the scope of 'available' could be added, but it's sufficient.

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

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

There are no parameters (schema coverage 100%), so the description doesn't need to add parameter info. Baseline 4 applies as the tool has zero parameters.

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

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

The description clearly states it lists available contact/signup forms (Wix Forms) and specifies the returned data (form name, ID, field definitions). It distinguishes from sibling tool submit_form by indicating this is 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?

The description explicitly says 'Use before submit_form to discover which fields to fill,' providing clear when-to-use guidance. It does not mention when not to use or alternative tools, but the context is sufficient.

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

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

No annotations are provided, so the description must carry the full burden. It discloses that the guides are curated, editorial, and ranked, implying read-only behavior. However, it does not mention any potential rate limits, authentication needs, or other behavioral traits.

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 with no wasted words. First sentence defines what the tool does; second sentence clarifies the use case. Highly concise 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?

For a simple list tool with one optional parameter, the description is fairly complete. It explains the nature of guides and when to use them. The lack of an output schema is acceptable as the return values are implicit.

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

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

With 100% schema description coverage, the description adds no additional meaning beyond the schema, which already documents the 'limit' parameter. The baseline 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 tool lists curated editorial guides ('best of' lists) with ranked places and editorial notes. It explicitly distinguishes itself as the best source for 'best X in this neighborhood' questions, differentiating from sibling tools 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?

The description provides clear guidance on when to use the tool: for finding 'best of' guides. It suggests the context ('best X in this neighborhood' questions) but does not explicitly state when not to use it or compare to 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?

Discloses return fields and notes that FLASH offers have a countdown deadline. No annotations provided, so description carries burden; it adequately conveys read-only behavior and special FLASH handling. However, does not mention if offers are filtered by time (e.g., expired) or pagination limits beyond the 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?

Three sentences with no waste: first states purpose, second lists return fields, third highlights special FLASH behavior. Perfectly concise 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?

For a simple list tool with two optional parameters and no output schema, the description sufficiently covers what the tool does and returns. Clarifies that it returns 'active' offers and mentions the countdown for FLASH. Could have added more about ordering or error cases, 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?

Schema description coverage is 100%, so both parameters (kind, limit) are documented in the schema. The description adds minimal value beyond the schema (mentions FLASH countdown deadline, which relates to the kind enum). Baseline 3 is appropriate.

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

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

Description clearly states the tool lists active promotions/deals in the neighborhood directory and specifies the return fields (discount label, promo code, CTA link, etc.). While it doesn't explicitly differentiate from sibling tools like list_pricing_plans, the domain ('offers') is specific enough. Score 4 for clear verb+resource.

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 this tool vs. alternatives such as list_pricing_plans or list_products. Usage is implied for promotions/deals, but no 'when-not' or alternative tools are 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, so description fully explains behavior: returns plan name, description, price, billing cycle, perks, and checkout URL. Understandably does not mention destructive actions as it's a read-only tool.

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

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

Concise, front-loaded with purpose, then distinguishes cases, then lists return fields. No wasted sentences.

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

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

For a simple listing tool with one optional parameter, the description is complete. It covers both usage modes and return content, filling the gap of missing output 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?

Schema has 100% description coverage, but the description adds significant meaning: explains `place_slug` comes from search_places, strongly recommends it, and clarifies the effect on results.

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 membership or subscription plans (Wix Pricing Plans). It distinguishes two modes: with `place_slug` (venue plans) and without (directory's own plans), which differentiates it from siblings.

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 recommends passing `place_slug` from search_places as the intended use, and warns that omitting it lists directory plans which most sites don't have. Provides clear context for usage.

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

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

No annotations; description only states it's a list operation without detailing behavioral traits like idempotency, authorization, or pagination.

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, clear and front-loaded, 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?

Returns fields are mentioned, but no output schema; lacks pagination or error handling details, but adequate 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%, so description adds no value beyond schema. 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 it lists products in Wix Stores, specifies returned fields, and is distinct from sibling list_* tools.

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

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

Implies usage for listing products but provides no explicit guidance on when to use vs alternatives or when not to use.

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

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

No annotations are present, so the description must fully convey behavior. It only states it lists profiles with no mention of pagination, authentication, side effects, or rate limits. The read-only nature is implied but not explicit.

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

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

The description consists of two sentences with no unnecessary words. It front-loads the purpose and provides examples 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?

Given no output schema, the description covers the return structure adequately ('name, profile URL, category, and any available metadata'). The tool is simple with one parameter, so no critical information is missing.

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

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

The input schema has 100% coverage with a single 'limit' parameter already described. The description adds value by specifying the return fields (name, profile URL, category, metadata), which helps understand the parameter's context.

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

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

The description clearly states the verb 'List' and the specific resource 'solo service-provider profiles' with examples (dog walkers, tutors). It defines what qualifies (no fixed physical location) and mentions return fields. This distinguishes it from sibling tools, none of which list profiles.

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

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

The description implies usage for listing solo providers but does not explicitly state when to use this tool vs alternatives like list_booking_services. No when-not or exclusion criteria are provided.

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

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

With no annotations provided, the description carries the full burden and fully discloses behavior: the restaurant is not notified immediately, a confirmation email is sent, the link expires in 24 hours, and the confirmation link is deliberately not returned to the caller. It honestly describes the tool as a request, 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?

The description is moderately concise, with key points front-loaded and emphasized with all caps. It is information-dense but could be slightly shorter; however, every sentence adds value and no fluff is present.

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 (asynchronous request, no output schema), the description is fully complete. It explains the flow, what the caller should do, and what the user can expect. No missing critical information.

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 does not add significant parameter-specific information beyond what the schema already provides (e.g., email description in schema already says 'the confirmation link is sent here'). The description reinforces the email usage but does not enhance semantic understanding of other parameters.

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

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

The description clearly states the tool requests a table at a restaurant and distinguishes it from a confirmed booking by explicitly stating 'This is a request, not a confirmed booking: the restaurant confirms out of band.' This differentiates it from the sibling tool 'create_booking' which likely handles confirmed bookings.

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

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

The description provides explicit instructions: use a real email belonging to the person you're acting for, tell the user to check their inbox, and notes the link expires in 24 hours. It also implies when not to use (if immediate confirmation needed, use create_booking) by contrasting with the behavior of 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?

The description discloses key behaviors: the hold is temporary, nothing is paid, a checkout URL is returned, and the hold expires on its own. No annotations are provided, so the description carries the full burden. It lacks details on error conditions or response format, but the core behavior is well-covered.

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, front-loading the main purpose and following with critical behavioral context. Every sentence adds value, with no redundancy or filler.

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

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

Given the tool's simplicity (2 required params, no output schema), the description covers purpose, usage, and behavior well. It mentions the returned checkout URL but not its structure; still, the information is sufficient for correct selection and 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% with parameter descriptions, so baseline is 3. The description adds context (max 10 tickets/ticket types) but does not significantly enhance parameter understanding beyond the schema's existing 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's purpose: 'Hold tickets for an event sold through this site (Wix Events) and return a checkout URL.' It specifies the verb 'hold' and resource 'tickets', and distinguishes from siblings like create_booking or create_checkout by emphasizing it's a temporary hold, not a purchase.

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

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

The description explicitly states when to use and when not: 'Only works for events this site sells directly — for events sold elsewhere (Sympla, Ingresse, Sesc), use the event's own ticketUrl instead.' It also provides constraints (max 10 tickets and 10 ticket types) and clarifies the temporary nature.

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 RSVP is not immediate, that a confirmation email is sent, and that the link expires in 24 hours. It also states the confirmation link is not returned to the agent. This covers key behavioral traits beyond the basic function.

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

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

The description is three sentences, extremely dense with information. It starts with the core purpose, then adds critical behavioral notes and user instructions. Every sentence earns its place with no redundancy or fluff.

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

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

The tool has 4 required params, no output schema. The description covers the key workflow (email confirmation, no guest list initially, link expiry). It does not explain return values, but the confirmation process is well-described. For a simple RSVP tool, it is mostly complete.

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

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

Schema coverage is 100%, so the schema already documents each parameter. The description adds slight context: for email, it says 'the confirmation link is sent here'; for event_slug, it says 'from list_events'. But firstName and lastName descriptions are minimal. Overall, the description adds marginal value beyond the schema.

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

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

The description clearly states the verb 'RSVP' and the resource 'free event on this site (Wix Events)'. It distinguishes from siblings like 'reserve_event_tickets' by specifying 'free event' and mentions 'Wix Events' which aligns with other event 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 explicit guidance: the RSVP is not immediate, requires email confirmation, and the agent should tell the user to check their inbox. It also advises using a real address belonging to the person the agent is acting for. However, it doesn't explicitly state when not to use this tool (e.g., for paid events), which is implied by 'free event'.

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 transparency burden. It discloses that the tool searches every menu item across all restaurants, groups by dish, and returns specific fields. It also notes that omitting the query lists top dishes. It does not mention potential limitations like pagination or rate limits, but for a search tool this is reasonable.

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

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

The description is three sentences, each earning its place. The first sentence states the core purpose, the second details behavior with an example, and the third provides a usage guideline. It is front-loaded and concise, without any 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 no output schema, the description explains the return format (grouped by dish, includes price, description, dietary labels, place URL) and covers both modes of usage (with and without query). It provides sufficient context for an AI agent to understand what the tool returns and how to use it.

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

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

Schema description coverage is 100%, so the schema already documents both parameters. The description adds value by explaining the query parameter's behavior with an example and stating that omitting it lists top dishes. For the limit parameter, the schema says 'Max dishes to return (default 20, max 50)', and the description does not add more, but overall the description enriches understanding.

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

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

The description clearly states the tool finds which restaurants serve a dish in a neighborhood, with grouping by dish and returning price, description, dietary labels, and place URL. The example with 'feijoada' and the instruction 'Use this for any "where can I eat X" question' make the purpose unmistakable. It distinguishes itself from siblings like search_places and 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?

The description provides explicit use cases: 'Use this for any "where can I eat X" question' and 'Omit the query to list the most-served dishes.' It does not explicitly state when not to use or list alternative tools, but the sibling list offers context. The guidance is clear enough for an AI agent to decide when to invoke 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?

With no annotations, the description carries full burden. It discloses typo-tolerance, accent-insensitivity, ranking by relevance, filter behavior, precomputed open_now, attributes array, delivery deep-links, and structured hours. No mention of rate limits or authentication, but the level of detail is high.

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 moderately long but well-structured with a clear initial purpose, followed by details on behavior, filters, and output. No superfluous sentences, though the list of amenity slugs could be slightly trimmed.

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

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

For a tool with 6 parameters (0 required) and no output schema, the description covers filter semantics, output fields, and common amenity slugs, providing sufficient context for the agent to use it 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%, so baseline is 3. The description adds value by explaining output fields (open_now, attributes, delivery, hours) and filter composition, which goes beyond the schema 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 searches for places (restaurants, cafes, shops) in a neighborhood, using a specific verb ('Search') and resource. It distinguishes from siblings like 'get_place' (single place) and 'search_dishes' (dishes only).

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

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

The description implies usage for searching places with various filters but does not explicitly guide when to use this tool versus alternatives like 'get_place' or 'search_dishes'. No when-not-to-use or exclusion criteria are given.

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

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

No annotations are provided, so the description carries the full burden. It states it submits a form and returns a submissionId, but does not disclose if it is destructive, requires authentication, or any other behavioral traits beyond the action.

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-load purpose and prerequisite, with no wasted words. Efficient and 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?

With two parameters and no output schema, the description covers prerequisites and return value. Referencing list_forms provides sufficient context for the agent to use the tool correctly.

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

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

Schema coverage is 100%, but the description adds value by stating that fields must match keys from list_forms and providing an example. This goes beyond the schema's basic property 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?

Description states 'Submit a form on behalf of the user (Wix Forms)', providing a clear verb and resource. The Wix Forms context differentiates it from sibling tools like create_booking or create_checkout, but no explicit sibling differentiation is given.

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 explicitly says 'Call list_forms first to get the formId and field keys', giving a clear prerequisite. It does not provide when-not-to-use or alternatives, but the context is sufficient.

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