Campo Belo

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

Without any annotations, the description fully discloses critical behavioral traits: the tool returns a checkout URL rather than confirming a booking, the slot is re-validated server-side, and the contact email is not verified. This compensates for the lack of annotations and gives the agent complete understanding of the tool's behavior.

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

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

The description is a single paragraph but is densely packed with value. It front-loads the most important caveat (payment required) and uses clear, direct language. It could be slightly more structured (e.g., bullet points), but it remains concise with no redundancy.

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

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

For a tool with 6 parameters, nested objects, no output schema, and a critical payment flow, the description covers all necessary context: preconditions (get_availability), postconditions (user must pay), behavioral quirks (slot rejection, email verification), and required parameter sourcing. It is complete enough for an agent to use correctly.

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

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

Although the schema covers 100% of parameters, the description adds essential semantics: it specifies that startDate and endDate must be exactly as returned by get_availability, serviceId must come from list_booking_services, and the contact object requires all fields. 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's purpose: 'Book an appointment slot at a venue (Wix Bookings)'. It uses a specific verb ('book') and resource ('appointment slot'), and the context differentiates it from sibling tools like create_checkout (payment flow) and get_availability (precondition check).

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

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

The description provides explicit usage guidance: it warns that nothing is booked until payment, instructs to call get_availability immediately before, and tells the agent to inform the user to open the checkout link. It could also explicitly state when not to use (e.g., if payment is not possible), but the current guidance is clear and actionable.

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 a URL is created and user clicks to complete payment. No annotations provided, so description carries full burden; lacks details on side effects, URL expiry, or permissions.

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

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

Two concise sentences front-loaded with key information. No unnecessary text.

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

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

Description is sufficient for a simple tool with one well-defined parameter. However, it does not mention return format (the URL itself), though output schema is absent.

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. Description adds no extra meaning beyond the schema's own descriptions. Parameter semantics are adequately conveyed by the schema alone.

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

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

Clearly states verb 'create', resource 'direct checkout URL', and context 'Wix Stores'. Distinguishes from sibling tools like create_booking or get_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?

Implicitly indicates use for payment checkout, and notes that no login is required on the AI agent side. Does not explicitly mention when not to use or alternatives.

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

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

No annotations provided, so description must inform behavior. It notes that slot times are in the venue's timezone, which is useful, but does not mention error cases or 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?

Two sentences, no redundant information. Efficiently conveys essential information without 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?

No output schema, so description is the only source for return expectations. It implies time slots but lacks details on structure, pagination, or error handling. Adequate for a simple tool but could be improved.

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 meaningful context: serviceId provenance, date format, and place_slug consistency beyond schema descriptions.

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

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

The description clearly states the tool retrieves available time slots for a bookable service on a given date, specifying the resource and action. It distinguishes from siblings like create_booking and list_booking_services.

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

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

Provides explicit instructions on how to pass parameters (serviceId from list_booking_services, date format, same place_slug). However, lacks when-not-to-use or alternatives.

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

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

No annotations provided, so description must cover behavior. It discloses return fields (names, prices, sale status, quantities) but does not explicitly state it is read-only or mention side effects. 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?

Three sentences that front-load the purpose, provide usage hint, and describe output. No fluff, but could be more concise by merging 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 tool with one parameter and no output schema, the description covers purpose, parameter source, and return format. 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% with a clear description of event_slug. Description repeats 'Pass the event slug from list_events' without adding new meaning beyond the schema. Baseline 3.

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

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

Clearly states it gets ticket types and prices for a specific event, specifying the context (Wix Events) and distinguishing from siblings like list_events and 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?

Tells when to use (to get ticket details) and explicitly instructs to pass the event slug from list_events, implying a sequence. Does not explicitly mention when not to use, but 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 exist; description mentions return fields but no behavioral details (e.g., caching, rate limits). Adequate given simplicity.

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

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

Single sentence, front-loaded with action and resource, 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?

Fully covers tool purpose and output for a parameterless, no-output-schema tool with no annotations.

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

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

No parameters, schema coverage 100%. Description adds value by listing return fields, exceeding baseline expectation.

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 Wix Loyalty, specifying return fields (program name, points currency, tier structure). Distinguished from sibling tools by naming the specific 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 when-to-use or alternatives provided. For a simple getter, it's clear but lacks guidance on selection among sibling 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?

Describes output fields (opening hours, ratings, address, neighborhood), giving a clear picture of what to expect. Since no annotations are present, it effectively communicates the read-only nature and scope of data. Could mention idempotency or safety, but acceptable.

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

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

Single sentence with all essential information, no extraneous content. Perfectly concise and front-loaded with key verb and resource.

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

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

For a simple retrieval tool with one required parameter and no output schema, the description covers the main output fields adequately. Could mention if there are additional fields not listed, 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 already describes the slug parameter with example. Description adds no extra semantic context beyond that. With 100% schema coverage, 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?

Clearly states it retrieves full details for a specific place by URL slug, listing included fields (opening hours, ratings, address, neighborhood). This distinguishes it from siblings like search_places (search) and get_reviews (just 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?

Implies usage when you have a specific URL slug, but does not explicitly contrast with alternatives like search_places for discovery or get_reviews for reviews. No when-not-to-use guidance.

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

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

The description discloses that the tool returns menu content (sections, dishes, descriptions, prices, dietary labels), which is useful. However, with no annotations, it does not state whether the operation is read-only, safe, or has any side effects, rate limits, or authentication needs. The description is somewhat transparent but lacks behavioral guarantees.

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 cover purpose, return content, and usage guidance. No redundancy or unnecessary detail.

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 adequately explains the return content (menus with sections, dishes, descriptions, prices, dietary labels). It also provides prerequisite context. Minor omissions (e.g., date scope, pagination) are acceptable for a simple lookup tool. The description is sufficiently complete for an agent to use correctly.

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

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

The single parameter place_slug is fully described in the schema (100% coverage), including an example and source. The description reinforces this by mentioning the prerequisite tools. Since schema coverage is high, the description adds no new parameter semantics beyond reinforcing, earning a baseline 3.

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

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

The description clearly states the tool's function: getting the food menu for a specific restaurant, including sections, dishes, descriptions, prices, and dietary labels. It distinguishes from siblings by specifying the resource (menu vs. place or reviews) and by mentioning prerequisites (place_slug from search_places or list_categories).

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

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

The description explicitly instructs the agent to use search_places or list_categories first to obtain the place_slug, effectively setting a prerequisite and excluding direct use without prior lookup. This provides clear when-to-use guidance and aligns with sibling tool 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 provided, so description carries burden. It discloses it returns specific fields and that reviews are published, but doesn't mention ordering, pagination beyond limit, or any side effects. Partially transparent.

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

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

Two concise sentences: first states purpose, second lists returned fields. No wasted words, front-loaded with key info.

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

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

For a simple read tool with one optional parameter and no output schema, the description covers core functionality. Could add ordering context but is generally sufficient.

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

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

Schema coverage is 100% with one parameter 'limit' fully described. The tool description adds no extra parameter meaning beyond what the schema provides. Baseline score 3.

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

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

The description clearly states the verb 'Get', resource 'published reviews for this site', and specifies the returned fields. It distinguishes itself from sibling tools like list_blog_posts by focusing on 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?

No guidance on when to use this tool vs siblings, no context about prerequisites or when not to use it. The description lacks explicit usage recommendations.

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 states the tool returns showtimes and mentions a prerequisite, but it does not disclose behavioral traits such as whether the operation is read-only (likely safe) or potential side effects. The description is decent but lacks explicit safety cues.

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

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

The description consists of two concise sentences: the first clearly states the core function, and the second adds return details and a prerequisite. No superfluous words or repetition. 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 the tool's simplicity (2 parameters, no output schema), the description covers the main aspects: what it does, what it returns, and a prerequisite. It lacks edge-case handling (e.g., missing movie, past date) but is complete enough for typical usage. Could be slightly more thorough, but still strong.

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

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

The input schema already fully describes both parameters (date with default today BRT, movie_slug from list_movies). The description adds no additional semantic value beyond what the schema provides, so the baseline score of 3 is appropriate.

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

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

The description uses a specific verb ('Get') with a clear resource ('showtimes for a specific movie at cinemas in this neighborhood, for a given date'). It also lists the return fields (session times, format, language), which distinguishes it from sibling tools like list_movies that list movies but not showtimes.

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

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

The description mentions a prerequisite ('Requires movies_enabled on this site') but does not explicitly state when to use this tool versus alternatives like list_movies or get_availability. The context implies you would use list_movies first to get a movie_slug, but this is not stated, leaving usage guidance merely implied.

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

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

With no annotations, the description fully discloses the tool's read-only behavior and output contents (directory info, time, weather). It lacks details on data freshness or rate limits, but the scope is adequately described.

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

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

The description is two sentences, front-loading the key outcome and providing concrete examples of use. Every word adds value; no redundancy.

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

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

Given no parameters and no output schema, the description is fairly complete: it lists the returned fields and provides usage examples. It could mention if time/weather are live or cached, but overall it meets the needs 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 tool has zero parameters, and the schema is empty. The description adds all semantic meaning by listing what information is returned. Per guidelines, baseline for 0 params is 4.

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

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

The description clearly states the tool 'returns basic information' including specific fields like name, locale, domain, local time, and weather. It differentiates itself from sibling tools by its unique combination of directory info and real-time 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?

The description explicitly suggests using the tool for 'what time is it there' or 'what's the weather like' queries, providing clear usage context. It does not mention when not to use or alternatives, but given the tool's specificity, 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?

No annotations exist, so the description must cover behavior. It indicates a read-only operation (listing) and specifies returned fields, but lacks details on pagination, sorting, rate limits, or error handling. Basic transparency 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?

Two concise sentences: the first states the action, the second lists return fields. No redundancy, front-loaded information, and every word adds value.

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

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

For a simple list operation with 2 optional parameters and no output schema, the description is adequately complete. It explains the operation and return fields, though 'recent' could be clarified for sorting order.

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

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

Schema coverage is 100% with clear descriptions for 'limit' and 'category'. The tool description does not add additional meaning beyond what the input schema already provides, so it meets the baseline for parameters.

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

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

Description clearly states the verb 'List', the resource 'recent published blog posts', and specifies the exact fields returned. It distinguishes from sibling tools like list_products or list_events by explicitly mentioning 'blog posts'.

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

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

The description implies usage for retrieving blog posts but offers no explicit guidance on when to use this tool over alternatives. No when-to-use or when-not-to-use conditions 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, the description fully discloses behavior: it lists services for all venues regardless of booking capability, explains the bookableViaMcp field and its implications (null id), and specifies return fields. No hidden side effects are likely for a read-only list operation.

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

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

The description is clear and front-loaded but somewhat lengthy. Every sentence adds value, though it could be slightly more concise without losing context. Still well-structured for an agent.

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

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

Given the simple tool with no output schema, the description fully covers the return fields, edge cases (non-bookable venues), and how to proceed. It provides all necessary context for an 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?

The schema has 100% coverage for the single parameter, but the description adds critical context: where to obtain place_slug (from search_places), its strong recommendation, and the functional difference between providing it or not (affects compatibility with create_booking).

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

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

The description clearly states the tool lists a venue's services with price and duration. It specifies the resource (venue services) and distinguishes between listing with and without a place_slug, differentiating it from sibling tools like create_booking or get_availability.

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 passing place_slug to get venue services, notes that this is the only form compatible with create_booking, and warns that omitting it yields directory services (rarely useful). It also advises checking bookableViaMcp and redirecting to bookingUrl when booking is unavailable.

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

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

No annotations, so description carries full burden. It explains the return content well but doesn't explicitly state it's read-only or idempotent. However, 'returns' implies no side effects. Adequate but could be more explicit.

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

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

Single sentence that front-loads the main purpose and then lists specifics. No wasted words, efficient.

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

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

Tool is simple with no parameters and no output schema. Description covers the return value comprehensively. No gaps given the tool's complexity.

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

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

No parameters; baseline is 4. Description adds no param info (none needed). Schema coverage is 100% with empty object. No further value needed.

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

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

Clearly states it returns the full category taxonomy with specifics like subcategories, labels, schema.org types, and place counts. Verb 'returns' and resource 'category taxonomy' are precise. Distinct from sibling list_* tools which handle 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?

Implicitly clear when to use: when needing the site's category structure. No explicit when-not or alternatives, but context makes it obvious. Could mention it's for the directory site's categories only.

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 carries full burden. It discloses that events within 7 days include weather forecast and that filter 'agora' is resolved live. This is good transparency, though it could mention more about caching, pagination, or error handling.

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

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

The description is two sentences that efficiently convey purpose, behavior, and usage examples. No superfluous information.

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

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

The description covers the basic purpose and key features but lacks details on return format, ordering, pagination, or error scenarios. Given no output schema, it could be more complete.

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

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

Schema coverage is 100%, and the description adds significant extra context, especially for the filter parameter (e.g., 'agora' excludes season runs, resolved live). This goes well beyond the schema descriptions.

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

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

The description clearly states the tool lists upcoming events with specific fields (date, venue, price, URL). It also mentions weather forecast for events within 7 days. However, it does not explicitly differentiate from sibling tools like list_blog_posts or get_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?

The description implies usage for retrieving event listings and gives examples for narrowing with filter, including 'agora'. However, it does not specify when not to use this tool or suggest alternatives.

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

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

No annotations are provided, so the description must carry the behavioral burden. It states it gets all FAQs grouped by category, which is basic. However, it does not mention potential for large data, permissions, or other behavioral details beyond the simple description.

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 short sentences. The purpose is front-loaded, and every sentence adds value. No unnecessary words or repetition.

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 zero parameters, no output schema, and a simple read operation, the description covers what it returns, the grouping, and the intended use case. It is complete and sufficient for an AI agent to select and invoke 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?

The input schema has no parameters (100% coverage), so the description does not need to add parameter details. It contributes additional context about grouping and use case, which is beneficial.

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 'FAQ questions and answers', and specifies grouping by category. It also distinguishes itself from sibling list tools by focusing on FAQs for answering common site questions.

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

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

The description explicitly says 'Use this to answer common questions about the site' with examples like opening hours, parking, policies. It does not provide when-not-to-use or alternatives, but the use case is clear and appropriate.

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 bears full burden. It indicates a read operation by listing forms, but doesn't explicitly state read-only, nor mention pagination, rate limits, or auth requirements. 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?

Three concise sentences, each with clear purpose: first states action, second describes return, third gives usage guidance. No redundancy, front-loaded with key info.

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

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

Given zero parameters and no output schema, the description fully captures tool functionality and integration context. No missing elements 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?

No parameters in schema, so description need not add param info. Baseline 4 applies as the description does not need to compensate for schema gaps.

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 available contact/signup forms, specifies it's for Wix Forms, and details return values (name, ID, field definitions). Distinguishes from siblings by explicitly mentioning use before submit_form.

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

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

Explicitly says 'Use before submit_form to discover which fields to fill,' providing clear when-to-use context and implicitly excluding situations where fields are already known.

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 carries full behavioral burden. It implies a read-only list operation but does not explicitly disclose side effects, permissions, or rate limits. The mention of 'ranked places with editorial notes' gives some output context 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?

Two sentences, no filler. First sentence defines purpose and content, second gives usage context. 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 list tool with one optional parameter and no output schema, the description covers purpose and usage context. It mentions the output nature (ranked with editorial notes) and use case. Minor gaps: no details on sorting, default behavior beyond limit, or response structure, but acceptable given 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 coverage is 100% for the single parameter 'limit', which is already well-described in the schema. The tool description adds no additional meaning beyond what the schema 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 resource 'guides', specifying 'curated editorial guides (best of lists)' with context 'ranked places with editorial notes'. This distinguishes it from sibling list tools like list_blog_posts or list_categories.

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

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

The description provides clear usage context: 'The best source for "best X in this neighborhood" questions.' While it doesn't explicitly state when not to use or list alternatives, this guidance effectively differentiates its purpose among siblings.

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

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

No annotations are provided, so the description must cover behavior. It discloses that the tool returns films with showtimes, coming-soon, or streaming, and lists returned fields. It does not mention destructive side effects, and none are implied, so it is reasonably 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 with no filler. The first sentence states the main purpose, and the second details the categories and returned 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?

Although no output schema is provided, the description lists the returned fields (title, genres, rating, runtime, URL). Combined with the input schema, this gives a clear picture. It does not mention sorting or pagination beyond the limit parameter, but it is adequate for a listing tool.

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

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

Schema coverage is 100% with both parameters already described in the schema. The description adds value by explaining what each status value means in context (e.g., 'now_showing' = films with upcoming showtimes). This goes beyond the schema enum labels.

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

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

The description clearly states the tool lists movies available in the neighborhood, distinguishing it from siblings like list_events or list_blog_posts. It specifies three movie categories (now-showing, coming-soon, streaming) and included fields.

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 the tool works 'only on sites with movies_enabled', providing a necessary precondition. It explains what each status filter means, helping the agent decide which filter to use. However, it does not explicitly mention when not to use or suggest alternatives.

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

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

No annotations provided, so description carries full burden. It describes return fields and FLASH behavior, but omits details like pagination, sorting, or whether only active offers are returned (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?

Two efficient sentences with no redundant information. Front-loaded with purpose and immediate return details.

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

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

Given no output schema and minimal params, the description covers core behavior and return fields. Could mention default ordering or limit behavior, 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% with clear descriptions for both parameters. The description adds context about return fields but does not enhance parameter meaning 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?

Description clearly states the tool lists active promotions and deals, specifies the returned fields (discount label, promo code, CTA link, validity window, business/place), and distinguishes 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?

No guidance on when to use this tool versus siblings like list_products or get_place. No exclusions or prerequisites mentioned.

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

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

No annotations are provided, so the description carries full burden. It describes the read-only nature (listing) but does not mention authentication requirements, rate limits, or whether the list is paginated. It is adequate but not comprehensive.

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

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

The description is a single, front-loaded sentence that conveys purpose and return data with no wasted words. It is efficient and well-structured.

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

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

For a parameterless tool with no output schema or annotations, the description covers the essential functionality and return values. It could mention potential limitations like pagination, but given the simplicity, 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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter information but compensates by detailing the returned fields, which is useful.

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

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

The description clearly states the action ('List') and resource ('membership or subscription plans offered by this site (Wix Pricing Plans)'), and lists the specific return fields (plan name, price, billing cycle, perks, checkout URL). This distinguishes it from sibling tools like list_products or list_blog_posts.

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

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

The description implies usage for retrieving pricing plans, but does not provide explicit guidance on when to use this tool versus alternatives, nor any conditions or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It lists returned fields (name, price, stock status, product type) but does not disclose pagination, sorting behavior, or error conditions. This is adequate but minimal.

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

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

The description is concise at two sentences, front-loaded with the main purpose, and contains no redundant or irrelevant 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?

Although no output schema exists, the description lists key return fields, which helps the agent understand the response. However, pagination semantics (e.g., offset, next page) are missing, given the limit parameter.

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

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

Schema coverage is 100% and both parameters have descriptions in the schema. The description adds no additional meaning beyond what the schema provides, 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?

The description clearly states the verb (list), resource (products), and context (Wix Stores store). It differentiates from sibling tools like list_blog_posts and list_categories by specifying product-related fields and the Wix Stores 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?

The description implies when to use (listing products) but lacks explicit guidance on when not to use or alternatives. No mention of related tools (e.g., search_dishes for non-store items) or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It declares the tool is idempotent (list) and specifies return fields, but lacks details on pagination, authentication, rate limits, or sorting behavior. Adequate for a simple 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 concise sentences front-loading purpose and return fields without unnecessary words. Efficient and well-structured.

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

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

Given no output schema and a simple input schema, the description adequately covers the tool's purpose and return fields. Missing details like sorting or pagination are minor for a basic list tool.

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

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

Schema coverage is 100% with one parameter (limit) well-described. The description does not add new information about the parameter beyond the schema, so 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?

Description clearly states the tool lists solo service-provider profiles, specifying the type (businesses without fixed physical location) and examples. It also mentions return fields, distinguishing it from siblings like list_booking_services and list_categories.

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

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

The description gives a specific scope for the tool (solo service providers without fixed location) but does not explicitly state when not to use or mention alternatives. It provides good context for selection among siblings.

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

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

Discloses key behavioral traits: restaurant not notified until confirmation link clicked, link expires in 24 hours, confirmation link not returned to agent, and that this is only a request. Since no annotations are provided, the description fully covers behavioral 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?

Three sentences that are front-loaded with the main purpose followed by key behavioral details. Every sentence adds essential information without redundancy.

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

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

Given the tool has 7 parameters, no output schema, and no annotations, the description covers the complete workflow including the confirmation process, expiry, and agent's responsibility. It provides sufficient context for an 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%, so baseline is 3. Description adds value by specifying that 'email' must be the guest's own email (link sent there) and that 'requestedAt' must be in the future. These are not explicit in the schema descriptions, improving parameter understanding.

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

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

Clearly states the tool requests a table at a restaurant, distinguishing it from a confirmed booking. The description differentiates from sibling tool 'create_booking' by emphasizing that this is a request, not a confirmed booking.

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

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

Provides clear when-to-use context: requesting a table. Includes instructions to use a real email and tell user to check inbox. Missing explicit when-not-to-use compared to siblings like 'create_booking', but the context is sufficiently 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?

Since no annotations are provided, the description fully carries the burden. It discloses that the hold is temporary, unpaid, and expires if checkout is not completed. This is critical behavioral information that an agent needs to know.

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 well-structured sentences. First sentence front-loads the action and result. Second sentence adds essential behavioral warnings and usage conditions. 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 covers purpose, usage, behavioral aspects, and limits. It does not mention error handling or return format beyond a checkout URL, but given the tool's simplicity and lack of output schema, 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 baseline is 3. The description does not add additional parameter details beyond what the schema already provides. It is acceptable but does not exceed the 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 the tool holds tickets for an event sold through Wix Events and returns a checkout URL. Distinguishes from siblings by specifying it only works for events sold directly on the site, as opposed to external ticket providers.

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 when to use (for events sold directly on this site) and when not to (for events sold elsewhere, use the event's own ticketUrl). Also states maximums (10 tickets, 10 ticket types). Provides clear context and alternatives.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It transparently describes the non-immediate effect: confirmation email sent, link expires in 24 hours, and the link is not returned to the caller. This is sufficient for a simple RSVP workflow.

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 relatively short (3 sentences) yet packs essential behavioral details. It front-loads the main action ('RSVP to a free event') and logically flows to the confirmation workflow and user instructions. Could be slightly tighter but earns its 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?

With 4 required parameters, no output schema, and no annotations, the description covers the key user-facing aspects: the need for a real email, the confirmation process, and the fact that the link is not returned. It is complete enough for an agent to correctly invoke and explain the tool to a user.

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 good descriptions for each parameter (e.g., email: 'The guest's own email — the confirmation link is sent here.'). The description adds minimal extra value beyond restating the email's role. Baseline 3 is appropriate as the schema already does the heavy lifting.

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 is for RSVPing to a free event on Wix Events. It distinguishes from sibling 'reserve_event_tickets' by highlighting the free nature and unique confirmation workflow. Verb 'RSVP' plus resource 'event' is specific and unambiguous.

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

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

Description explicitly explains that no one is on the guest list yet and outlines the confirmation email process. It instructs the user to check their inbox and use a real address. However, it does not directly compare to siblings like 'reserve_event_tickets' or note when not to use this tool.

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

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

No annotations are provided, so the description fully explains the tool's behavior: searches across all restaurants, groups by dish, and returns price, description, dietary labels, and place URL. Omitting query returns most-served dishes. Additional details like pagination or rate limits are not covered but are not critical.

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: the first states purpose and scope, the second details inputs and output. No unnecessary words, front-loaded with key information.

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

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

Given no output schema, the description adequately summarizes the return value (restaurants with price, description, dietary labels, place URL). Parameters are fully covered. The sibling tools are all read/list operations, and this tool fits the context well.

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 meaningful context: explains that 'query' is a dish name or part of it, and omitting it lists top dishes. Examples like 'feijoada' and 'pizza margherita' clarify usage beyond the schema's brief 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 specifies the verb 'search' and the resource 'dishes', clearly stating it finds which restaurants serve a dish in a neighborhood. It distinguishes from sibling tools like 'search_places' and 'get_restaurant_menus' by focusing on dish-level search across all restaurants.

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

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

Explicitly states when to use: for 'where can I eat X' questions. Describes behavior when query is omitted (list top dishes). Does not explicitly mention alternatives, but the context of sibling tools makes it clear.

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

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

Discloses important behaviors: accent-insensitive and typo-tolerant matching, relevance ranking, optional filters, and structured opening hours format. No annotations are provided, so the description carries full burden and does so effectively, though it omits potential rate limits or error responses.

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

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

Extremely concise with two well-structured sentences. The first sentence states the purpose, and the second provides key behavioral details. Every sentence is informative with no redundancy.

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

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

Given no output schema, the description only partially explains the return value by detailing opening hours. It does not mention other fields like name, address, ratings, or distance, leaving some ambiguity about the output structure for a search tool.

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

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

Schema covers all parameters with descriptions, but the description adds value with concrete examples (e.g., 'acai' finds 'Açaí') and explains the opening hours format beyond the schema. It also clarifies the optional nature of filters.

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 searches for places like restaurants and cafes, with specific behavior for accent-insensitivity and typo-tolerance. Does not explicitly differentiate from sibling tools like get_place or search_dishes, but the purpose is specific enough.

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 versus alternatives such as get_place or list_categories. The description implies usage for text-based place search, but lacks clear recommendations or exclusions.

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

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

No annotations are provided, so the description must cover behavioral traits. It identifies a write operation and return value but does not disclose potential side effects, idempotency, or permission requirements. Adequate for a simple submission but lacks deeper insights.

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. Front-loaded with the primary action, then prerequisite, then result. Very 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 two parameters, simple input without nested objects beyond key-value pairs, and no output schema, the description is mostly complete. It covers the workflow and return value, though it could note error cases or state that the submission modifies data.

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

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

Schema coverage is 100%, but the description adds value by explaining how to obtain formId and field keys (via list_forms) and provides an example for the fields parameter. This enhances understanding beyond the schema.

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

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

The description clearly states the action ('Submit a form'), the resource ('Wix Forms'), and the outcome ('Returns a submissionId'). It distinguishes from sibling tools like list_forms by indicating it is the submission step.

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 retrieve the formId and field keys, providing clear guidance on prerequisite and workflow.

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