Bom Retiro

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

With no annotations, description fully discloses critical behaviors: nothing is booked until payment, returns checkout URL, slot re-validated, contact email not verified. Exceptionally transparent.

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

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

Front-loaded with key warning, but slightly lengthy. Every sentence earns its place; good structure overall.

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

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

Given 6 parameters, nested objects, no output schema, and no annotations, the description is fully complete: explains workflow, prerequisites, and behaviors. No gaps.

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

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

Schema coverage is 100%, but description adds meaningful context: explains contact field requirements, startDate/endDate origin, place_slug source, and resourceId optionality. Adds value beyond schema.

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

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

Clearly states it books an appointment slot at a venue, distinguishing it from other actions by emphasizing the checkout/payment workflow.

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 before this tool and warns of slot re-validation; tells user to open the checkout URL. Provides clear when-to-use and follow-up steps.

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

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

With no annotations, the description carries full burden. It discloses the creation of a URL and the user's payment flow, but does not mention side effects, state changes, or potential errors. 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?

Two sentences, front-loaded with the action, no wasted words. Highly 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 simple input (one array parameter) and no output schema, the description covers the essential purpose and flow. It could optionally mention the return value (the URL), but it is not a significant gap.

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

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

Schema coverage is 100%, so the description does not need to compensate. It adds context about the URL and user action, which is helpful but does not deepen understanding of the parameters beyond what the schema provides.

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

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

The description explicitly states the verb 'Create', the resource 'direct checkout URL', and the domain 'Wix Stores'. It clearly distinguishes from sibling tools like list_products or create_booking by focusing on payment/checkout.

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

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

It provides helpful context that the user clicks the URL to complete payment and that no login is required on the AI agent side, but it does not explicitly state when to use this tool versus alternatives like request_reservation or create_booking.

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

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

No annotations are provided, so the description must cover behavioral traits. It discloses a key insight: "slot times are returned in the VENUE's timezone, which is not necessarily the directory's." This adds behavioral context beyond mere operation. However, it does not mention other traits like idempotency or data volume limits.

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

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

The description is concise at two sentences, front-loaded with purpose and then instructions. No unnecessary words; every sentence contributes value.

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

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

Given that no output schema exists, the description is reasonably complete by stating what is returned (available time slots). It explains the source system (Wix Bookings) and all three parameters. It lacks details on the response format or pagination, but for a slot-listing tool, this may be 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?

Schema coverage is 100%, so the baseline is 3. The description adds semantic value by explaining how to obtain the place_slug ('use the same one passed to list_booking_services') and clarifying that slot times are in the venue's timezone, which affects interpretation of the date parameter.

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

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

The description clearly states the tool's purpose: 'Get available time slots for a bookable service on a given date (Wix Bookings).' It specifies the resource (bookable service), verb (get), and scope (on a given date), distinguishing it from siblings like list_booking_services 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?

The description provides clear usage instructions: pass the serviceId from list_booking_services, a date in YYYY-MM-DD format, and the same place_slug used earlier. It also notes the timezone behavior, guiding effective use. It does not explicitly state when not to use the tool or suggest alternatives, but the context with siblings 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 return values (ticket names, prices, sale status, quantity left). No annotations provided, but the description adequately conveys it is a read operation without side effects.

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

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

Two sentences, no wasted words. First sentence defines purpose, second covers usage and output. Structured effectively.

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

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

Given simple tool with one parameter and no output schema, description is largely complete. Could mention error cases or auth, but not essential for basic use.

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; description reinforces the schema but adds no new meaning beyond 'event slug from list_events'. Meets 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?

Clearly states the tool gets ticket types and prices for a specific event, using the verb 'Get' and specific resource. Distinguishes from sibling tools like list_events by referencing event slug.

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

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

Provides clear context: 'Pass the event slug from list_events' implies a chaining pattern after list_events. Lacks explicit when-not-to-use or alternative tools, but sufficient for guidance.

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

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

No annotations are provided, so the description carries full burden. It discloses the return values but omits behavioral traits such as idempotency, caching, or authentication requirements. For a simple read-only getter, this is minimally 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?

Two concise sentences: the first states the purpose, the second details the return value. Every sentence earns its place with no waste.

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, the description fully covers what the tool does and what it returns. No gaps remain given the tool's simplicity.

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

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

There are zero parameters, so baseline is 4. The description adds value by outlining the returned fields, which compensates for the lack of an output schema. No parameter details are 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?

The description clearly states it retrieves loyalty/rewards program details for the site, listing specific return values (program name, points currency, tier structure). The verb 'get' is specific, and the resource is unambiguously 'loyalty info', distinguishing it from unrelated sibling tools.

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

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

No explicit guidance on when to use or not use this tool. Since it is the only loyalty-focused tool among siblings, usage is implied, but there are no exclusions or context about prerequisites 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 convey behavioral traits. It implies a safe read operation but does not disclose authentication needs, rate limits, or any side effects. 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?

Single sentence, front-loaded with the key action, no fluff. Every word earns its place.

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

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

Given one parameter, no output schema, and no annotations, the description sufficiently covers the purpose and return fields. Could be slightly more explicit about what constitutes 'full details', 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 coverage is 100% with one parameter (slug). Description adds clarity by specifying it's a URL slug and provides an example, going beyond the schema's own 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?

Description clearly states the tool retrieves full details for a specific place by URL slug, listing included fields (opening hours, ratings, address, neighborhood). This distinguishes it from sibling tools like search_places or get_reviews.

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

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

No explicit guidance on when to use this tool versus alternatives. While context implies it's for fetching a single place's details, there is no when-not-to-use or mention of 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 provided, so description must disclose behavior. It accurately describes the return type (menus with sections, dishes, etc.) without omitting important aspects. Lacks mention of authentication or rate limits, but acceptable for a read-only retrieval tool.

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

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

Two sentences, no wasted words. First sentence states core purpose, second provides usage context. Well-structured 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?

Provided context (single required param, no output schema) is fully covered by the description. Lists expected content (sections, dishes, prices, labels) without gaps. No further elaboration needed.

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

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

Parameter place_slug is fully documented in schema (100% coverage). Description adds example and source context ('from search_places or a place URL'), enhancing understanding beyond the schema.

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

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

Description clearly states it retrieves food menus with detailed content (sections, dishes, prices, dietary labels) for a specific restaurant. Distinguishes from sibling tools like search_dishes and get_place by specifying the resource and output.

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

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

Explicitly advises using search_places or list_categories first to obtain the required place_slug, providing clear context for proper invocation. No direct exclusion of alternatives, but sufficient guidance is given.

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

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

No annotations are provided, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or side effects. While the operation is implicitly read-only, explicit behavioral context is missing.

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, focused sentence of 18 words. It is concise and front-loaded with the key action and resource, with no redundant or unnecessary content.

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

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

For a simple read tool with one parameter and no output schema, the description is reasonably complete. However, it lacks details on possible response formats, pagination behavior, or error conditions, which would be helpful for an agent.

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

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

The only parameter, 'limit', is fully described in the schema with default and max values. The description adds no extra meaning beyond the schema. With 100% schema coverage, a 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 (Get), the resource (published reviews for this site), and the data returned (reviewer name, rating, title, content). It effectively distinguishes itself from sibling tools, none of which appear to retrieve reviews.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The context signals show 27 sibling tools, but no comparative information is given.

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

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

No annotations provided, so description carries full burden. It discloses that results include cinema, session times, format, and language, but doesn't mention potential side effects, auth details beyond site requirement, or pagination. Adequate for a read tool.

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

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

Two concise sentences, front-loaded with action and scope. No unnecessary words, every sentence adds value.

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

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

No output schema, but description explains return format sufficiently. Could mention that it returns only neighborhood cinemas, but overall adequate for a 2-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?

Schema coverage is 100%, baseline 3. Description adds meaning: movie_slug from list_movies with example, date format and default. Provides context beyond schema, enhancing usability.

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 retrieves showtimes for a specific movie at neighborhood cinemas on a given date, specifying returned data types. It distinguishes from siblings like list_movies or get_event_tickets by focusing on showing times.

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 prerequisite 'Requires movies_enabled on this site', and context implies use after list_movies. No explicit when-not-to-use or alternative comparisons, but sufficient guidance.

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

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

No annotations are provided. The description discloses that it returns current local time and weather, implying no side effects. However, it does not explicitly state read-only or auth requirements, though not needed for this simple info retrieval.

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 purpose and usage context. Excellent conciseness.

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

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

Given no parameters, no output schema, and a simple tool, the description fully explains what the tool returns and when to use it. No gaps.

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

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

There are 0 parameters. The description adds meaning beyond the empty schema by detailing the returned fields, which is valuable. 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 specifies the verb 'returns' and the resource 'basic information about this neighborhood directory', listing specific fields including local time and weather. It distinguishes itself from sibling tools which handle bookings, events, etc.

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 any "what time is it there" or "what's the weather like" context'. Does not provide exclusions, but given the tool's simplicity, it 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 full burden. It describes the tool as listing 'recent' posts and returning specific fields, but does not clarify ordering, pagination, or the definition of 'recent'. For a simple list tool, 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 two sentences: first states the action and resource, second lists return fields. 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 the tool's simplicity (2 optional params, no output schema), the description covers basic purpose and returns. However, it lacks details on ordering, default limit, and edge cases like empty results. Adequate but 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% (both limit and category have descriptions). The description does not add significant meaning beyond what the schema already provides, so a 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 it lists recent published blog posts for the site (Wix Blog) and specifies the return fields. It distinguishes from sibling tools like list_products or list_events by explicitly naming the 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?

The description does not provide explicit guidance on when to use this tool vs alternatives, nor does it mention when not to use it. The purpose is implied as the go-to for listing blog posts, but no exclusions or alternatives 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?

Despite no annotations, description fully discloses behavior: lists services for every venue (even non-bookable), explains the bookableViaMcp field meaning, and notes that omitting place_slug yields directory services (usually empty). No contradictions.

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

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

The description is detailed and front-loaded with the core purpose, but slightly verbose with extra explanatory phrases. Still, every sentence adds value; minor room for tightening.

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?

Without output schema, the description compensates by listing return fields (name, description, price, duration, bookableViaMcp) and explaining edge cases like non-bookable venues. Complete enough for accurate 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 a well-described parameter. Description adds significant context: origin of value (search_places), strong recommendation to use it, and the consequence of omission. Goes beyond 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?

The description explicitly states the tool lists a venue's services with price and duration, and distinguishes between listing a specific venue's services (via place_slug) and the directory's own services. It clearly separates this from sibling tools.

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

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

Provides explicit guidance: pass place_slug from search_places for venue services (the common case), warns against omitting it, and advises to point users to bookingUrl or venue page when bookableViaMcp is false. Clearly contrasts with alternatives like create_booking.

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

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

No annotations, so description bears full weight. Accurately states read-only nature and return structure. Could add details about response size or absence of pagination, but 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?

Single sentence with all key info front-loaded. 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?

No output schema but description covers return content. Missing pagination or limit info, but likely unnecessary for a fixed taxonomy.

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

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

No parameters, schema coverage 100%. Baseline 4; description need not add 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?

Description clearly states the tool returns the full category taxonomy, specifying fields (top-level groups, subcategories, localized labels, schema.org types, live place counts). Distinguished from sibling list tools by being site-specific category hierarchy.

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. Implies use for category browsing, but lacks exclusions compared to other list tools like list_products or list_blog_posts.

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 that events within 7 days include a weather forecast (condition + temp) and that 'agora' filter is resolved live on every call. This adds behavioral context beyond just the input schema.

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

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

Three sentences, front-loaded with core purpose, then details. No unnecessary words. Every sentence adds value.

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

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

No output schema, so description covers return fields (date, venue, price, URL, weather). It explains all 3 parameters and their effects. For a list tool with no output schema, the description is remarkably 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%, baseline 3. The description adds significant meaning to the 'filter' parameter by explaining each enum value (e.g., 'agora' = on stage now, 'gratis' = free). It also clarifies 'upcoming_only' default behavior and 'limit' meaning. Adds high value 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?

Description clearly states it lists upcoming events in a neighborhood with specific fields (date, venue, price, URL). It also includes a special weather forecast feature for events within 7 days. This verb+resource combination is distinct from sibling tools like list_movies 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?

Provides explicit guidance on when to use the 'filter' parameter, especially 'agora' for live events. It explains that 'agora' is resolved live vs. cached, implying when this filter is useful. Lacks explicit 'when not to use' or comparisons to alternatives, but the context is clear.

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

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

No annotations provided. Description only states what is returned, not behavioral traits like idempotency, rate limits, or authorization. Falls short for a tool without annotations.

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, second sentence adds usage guidance. 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?

Covers purpose and usage context. No output schema or complex behavior needed. Lacks detail on response volume (e.g., pagination), but given zero parameters, simplicity justifies completeness.

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

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

No parameters; schema coverage 100%. Baseline 4 per rules. Description adds no parameter information because none exist, but that's acceptable.

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

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

States verb (Get), resource (FAQ questions and answers), and scope (for this site) clearly. Grouped by category adds detail. Different from siblings as no other tool covers FAQs.

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

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

Explicitly tells when to use: 'Use this to answer common questions about the site — opening hours, parking, policies, etc.' Does not mention when not to use or suggest alternatives, 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 provided, so the description carries the burden. It correctly indicates a read operation with return values, but lacks explicit mention of no side effects 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?

Two sentences with clear structure: first states purpose and platform, second provides usage guidance. 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, no output schema, and no annotations, the description fully covers what the tool does, what it returns, and when 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?

No parameters are defined; schema coverage is 100%. The description adds no parameter details but adds context about returned data, meeting the baseline for zero-parameter tools.

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

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

The description clearly specifies the tool lists contact/signup forms on Wix Forms, returns form name, ID, and field definitions, and distinguishes from sibling tool submit_form by advising its use beforehand.

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

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

The description explicitly states 'Use before submit_form to discover which fields to fill,' providing clear usage context. It does not exclude other uses but given the straightforward nature, 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 are provided, so the description carries full burden. It describes the tool as listing guides, implying a read-only operation, but does not explicitly state safety, permissions, or side effects. For a simple list, this is adequate but could be more explicit.

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

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

The description is two sentences, front-loaded with the core action ('List curated editorial guides'), followed by context. Every sentence adds value without redundancy.

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

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

Given the tool's simplicity (one optional parameter, no output schema), the description effectively conveys purpose and usage. It explains the content (guides with rankings and notes) and typical use case, which is sufficient for selection.

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 the 'limit' parameter well-documented. The description adds no additional meaning for parameters beyond listing functionality, so it does not enhance the schema. 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 lists curated editorial guides ('best of' lists) with ranked places and editorial notes. It distinguishes itself from siblings by focusing on guides rather than blog posts, categories, etc., and provides a specific use case ('best X in this neighborhood').

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

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

The description advises using it for 'best X in this neighborhood' questions, which is helpful context. However, it does not explicitly mention when not to use it or list alternatives, though the sibling tools provide implicit 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 disclose behavioral traits. It does not explicitly state whether the tool is read-only, destructive, or requires authentication. It describes the output fields but omits error conditions or side effects. The description is adequate but leaves gaps.

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 focused sentences. The first sentence states the core purpose and constraint. The second sentence lists return categories and included fields. No unnecessary words or repetition. Front-loaded with the primary action.

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

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

Given the tool has no output schema, the description adequately explains the return types (now-showing, coming-soon, streaming) and included fields (title, genres, TMDB rating, runtime, detail URL). It also mentions the 'neighborhood' and 'movies_enabled' context. The two optional parameters are covered by the schema. The description is sufficient for selecting and invoking the tool.

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

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

Schema description coverage is 100%, so the input schema already explains both parameters (limit and status) with descriptions. The tool description reiterates the status meanings but adds no new information beyond what the schema provides. Baseline 3 is appropriate.

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

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

The description clearly specifies 'List movies available in this neighborhood' with a specific verb and resource. It distinguishes from sibling tools like list_events by focusing on movies and mentioning 'movies_enabled' sites. The return categories (now-showing, coming-soon, streaming) and included fields are explicitly stated.

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

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

The description provides context ('only on sites with movies_enabled') and explains the status filter options. However, it does not explicitly state when to use this tool versus other listing tools (e.g., list_events) or provide when-not scenarios. The context is clear but lacks exclusion guidance.

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

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

With no annotations, the description adds behavioral context beyond the schema by listing return fields and noting FLASH offers have countdowns. However, it does not state safety traits like read-only nature, which is acceptable for a listing tool.

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

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

Three concise sentences front-loading the purpose, listing return fields, and highlighting a special case. Every sentence adds value with no redundancy.

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

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

Given no annotations or output schema, the description effectively covers purpose, return data, and the FLASH variant. It lacks details on ordering or pagination beyond the limit parameter, but is sufficient for a straightforward listing tool.

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

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

Schema coverage is 100% with parameter descriptions. The description adds modest value by explaining FLASH offers, but does not significantly enhance parameter understanding beyond the schema.

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

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

The description clearly states the tool lists active promotions and deals, specifying it's for a neighborhood directory. It distinguishes itself from sibling list_* tools by focusing on offers and detailing return fields (discount label, promo code, etc.).

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, but the name and description imply it's for offers. Sibling tools are for different resources, so context is adequate but lacks exclusions.

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

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

Without annotations, the description partially carries the burden of behavioral disclosure. It states what data is returned (plan details, checkout URL) but does not specify whether the operation is read-only, requires authentication, or has any side effects. For a simple list tool, 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 consists of two terse sentences. The first sentence front-loads the action and resource, and the second sentence details the output. Every word adds value, with no redundancy.

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

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

Given the simplicity (no parameters, no output schema) and the low complexity, the description adequately covers what the tool does and returns. However, it could be slightly more complete by noting that all plans are listed (e.g., 'Returns all available plans'). Nevertheless, it provides sufficient information for the agent to 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?

There are no parameters, so the input schema fully covers the parameter space (100% coverage). The description does not add parameter information, but none is needed. Baseline score of 4 for zero-parameter tools 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 action ('List') and the resource ('membership or subscription plans'). It also specifies the returned fields (plan name, price, billing cycle, perks, direct checkout URL), making the purpose unambiguous. The tool is distinct from sibling listing tools which cover different entities like products, blog posts, events, etc.

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

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, filtering, or exclusionary criteria. For a tool with many siblings, this absence leaves the agent without context to differentiate usage scenarios.

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 should cover behavioral aspects. It only states it returns specific fields but does not mention that it is a read-only operation, authentication requirements, or pagination behavior (though 'limit' param is in schema).

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

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

Two short sentences with no unnecessary words. Immediately states the tool's purpose and output.

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 function and return fields. However, given the complexity (no output schema, simple params), it is minimally complete. Missing context about when to use or permissions.

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 (q, limit) described. The description does not add extra meaning beyond the schema, so 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 action ('List'), the resource ('products'), the context ('in this site's store (Wix Stores)'), and the return fields ('name, price, stock status, and product type'). This distinguishes it from sibling list tools like list_blog_posts or list_booking_services.

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

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

No guidance is provided on when to use this tool versus alternatives, such as list_offers or get_place. The description does not mention exclusions or prerequisites.

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

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

No annotations are provided, so the description carries the full burden. It states the tool returns specific fields and implies read-only behavior, but does not disclose authentication needs, rate limits, or whether pagination is supported. 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?

Two sentences that are direct and front-loaded. Every word adds value 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?

For a simple list tool with one optional parameter and no output schema, the description covers the purpose, target profiles, and returned fields. It could mention pagination or sorting, but the core information is present.

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 only parameter (limit) is fully described in the input schema with a default of 50. The description adds no additional information beyond the schema. With 100% schema coverage, the baseline is 3, and no extra value is provided.

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, specifies they are businesses without a fixed physical location, gives examples (dog walkers, tutors), and lists returned fields (name, profile URL, category, metadata). This distinguishes it from sibling list tools like list_products or list_events.

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

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

No explicit when-to-use or when-not-to-use guidance, nor mention of alternatives among the many sibling list tools. The description implies the tool is for solo service providers without a physical location, but does not clarify when to choose this over other list tools.

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

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

No annotations provided, so the description fully discloses the behavioral flow: the request is held, a confirmation email is sent, the link expires, and the restaurant confirms out of band. This covers all critical user-facing behavior beyond typical 'create' semantics.

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 but includes an all-caps warning that emphasizes the key point. It is front-loaded with the most important information (the reservation is not final). Slightly verbose but efficient overall.

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 reservation request tool with no output schema, the description thoroughly explains the entire flow, what the agent should tell the user, and the constraints on the email address. No gaps in contextual information needed for correct invocation.

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

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

Schema description coverage is 100%, so each parameter is well-documented in the schema. The description adds minimal extra meaning beyond the schema, except reinforcing that the email must be the guest's own. With high schema coverage, baseline 3 is appropriate.

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

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

Clearly states the tool requests a table at a restaurant and distinguishes itself from a confirmed booking by emphasizing this is a pending request. The description differentiates from siblings like 'create_booking' by explicitly noting the restaurant is not notified yet.

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

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

Provides explicit guidance: the request is held pending email confirmation, the user must check their inbox, the link expires in 24 hours, and the confirmation link is deliberately not returned. Also warns to use a real email address belonging to the person being acted for.

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

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

With no annotations, the description fully discloses key behavioral traits: the hold is temporary, nothing is paid, human interaction needed, hold expires automatically, and limits on tickets and ticket types. This is comprehensive 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 brief: three sentences that front-load the core purpose and return value, then add critical behavioral and usage notes. No wasted words.

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

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

Given no output schema and no annotations, the description covers purpose, usage, behavior, and limits effectively. The only gap is the lack of detail on the response structure beyond 'return a checkout URL', but the tool is simple enough that this is acceptable.

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

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

Schema description coverage is 100%, so baseline is 3. Description adds value by stating the maximum of 10 tickets and 10 ticket types per reservation, which is a constraint not fully captured in the schema's per-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?

Description clearly states the tool holds tickets for events sold via Wix Events and returns a checkout URL. It explicitly distinguishes from sibling tools by noting it only works for events sold directly by this site, differentiating from other event-related tools like get_event_tickets or rsvp_event.

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

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

Provides explicit when-to-use and when-not-to-use guidance: only for events sold directly by this site, and for external events recommends using the event's own ticketUrl. Does not directly compare to all siblings like create_checkout but gives clear context for appropriate use.

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

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

No annotations are provided, so the description fully carries the burden. It discloses the full flow: nobody is on the guest list, confirmation email, click link to complete, 24-hour expiry, and that the link is not returned. This is 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 concise at three sentences, all essential, with key information front-loaded. No wasted words.

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

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

Given no output schema, the description adequately explains the tool's behavior and outcome. It covers the confirmation flow and user instructions, making it complete for the tool's simplicity.

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

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

Schema coverage is 100% with clear parameter descriptions. The overall description adds context about email belonging to the real person but does not significantly add beyond schema. Baseline 3 is appropriate.

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

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

The description clearly states 'RSVP to a free event on this site (Wix Events)', providing a specific verb and resource. It distinguishes from sibling tools like reserve_event_tickets (for paid events) and list_events.

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

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

The description explains the RSVP process, including that a confirmation email is sent and the user must check their inbox. It implies when to use (free events) and not to use (if immediate confirmation is needed), though it does not explicitly name alternatives.

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

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

Describes the search scope (all menu items, grouped by dish), the result fields (price, description, dietary labels, URL), and the special behavior when query is omitted. Lacks details on authentication or rate limits, but no annotations provided to contradict.

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 that front-load the purpose, then detail results and use case. No wasted words; every sentence provides actionable information.

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

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

For a search tool with 2 parameters and no output schema, the description covers the input behavior, expected output fields, and optional usage. Lacks return value details but is still sufficient 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?

Schema covers both parameters (query, limit) with descriptions. The description adds value by explaining the effect of omitting query (list top dishes) and providing example queries, beyond what schema states.

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 that the tool finds which restaurants serve a dish, using the verb 'Find' and specifying the resource 'dishes'. It distinguishes from siblings like 'search_places' by focusing on dish-level queries.

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

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

Explicitly tells the agent when to use this tool: 'Use this for any "where can I eat X" question.' It also implies an alternative by omission (not searching places) and shows how to list top dishes.

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

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

With no annotations, the description carries the full burden. It explains that query matching is accent-insensitive and typo-tolerant, and details the format for returning opening hours (Google Maps periods format with day 0=Sun–6=Sat, time HHMM). It does not mention authentication needs or rate limits, but the key behaviors are transparent.

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

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

The description is two sentences: the first states the purpose and optional filters, the second explains search behavior and output details. Every sentence is necessary and well-structured, with no wasted words. Front-loaded with the main action.

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

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

Given 4 optional parameters, no output schema, and no annotations, the description explains input behavior and returns structured opening hours but does not describe the overall response structure. The agent cannot know what other fields (e.g., name, address, rating) are returned, which may limit its ability to use the results without additional tool calls.

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 that 'q' is matched against name and address and is typo-tolerant, going beyond the schema's description. Other parameters like 'limit', 'category', and 'neighborhood' are simply restated, but the added detail for 'q' raises the score.

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

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

The description clearly states the tool searches for places like restaurants, cafes, and shops in a neighborhood, using a specific verb 'Search' and resource 'places'. It distinguishes from sibling tools like 'search_dishes' and 'get_place' by focusing on general place search.

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 by stating the tool searches for places and optionally filters by category or neighborhood, but it does not explicitly state when not to use it or contrast with alternatives like 'get_place' or 'list_categories'. Steer toward 'search_places' when you need a broad search; however, no direct guidance is given.

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

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

No annotations provided, so description carries full burden. It correctly states the tool returns a submissionId and implies data creation ('on behalf of the user'), but does not detail side effects or authorization requirements. No contradictions.

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

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

Two sentences, no wasted words. Front-loaded with purpose and key action, followed by usage hint and return value. Ideal length.

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 explains the return behavior (submissionId), names the prerequisite tool, and covers the two parameters adequately. Given no output schema and moderate complexity, it is fully informative.

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

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

Schema coverage is 100%, and the description adds significant context: explains the prerequisite (list_forms), gives an example for fields, and ties formId to the prerequisite. This goes 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 action ('Submit a form') and the resource ('Wix Forms'), with specific verb and noun. It distinguishes from siblings by naming the platform and referencing list_forms as prerequisite.

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

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

Explicitly instructs to call list_forms first to obtain formId and field keys, providing clear usage context. Lacks explicit alternatives or when-not-to-use, but the specific purpose naturally limits misuse.

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