Vila Mariana

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

No annotations provided, so description carries full burden. It discloses that the slot is re-validated server-side, that a taken slot is rejected, and that the booking stays off the calendar until payment is completed via the checkout URL.

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 dense but clear, front-loading the key behavior. A bit long but every sentence adds value; could be slightly better structured with line breaks.

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 explains the output (checkout URL) and the workflow (prerequisite, verification, payment step). Provides enough context for correct tool 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% (each parameter described). Description adds usage-critical context: start/end dates must be exactly as returned by get_availability, and all three contact fields are required. This goes 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 it books an appointment slot at a venue, and distinguishes itself by emphasizing that nothing is booked until payment, setting it apart from siblings like create_checkout.

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

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

Provides explicit instructions: call get_availability immediately before, and tell the user they must open the returned checkout URL to complete payment. Also notes that the contact email is not verified at this step.

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. Discloses that the agent doesn't need login and the user completes payment, but omits details like URL expiration or side effects. Adequate for a simple 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, first states purpose, second adds behavioral note. Every sentence earns its place, 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?

Simple tool with one parameter. No output schema but describes return (checkout URL). Nearly complete; could explicitly mention return format.

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

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

Schema covers 100% of parameters with descriptions. Description adds valuable context (productId from list_products) 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?

Clearly states the tool creates a direct checkout URL for store products, specifying the context (Wix Stores) and the outcome (user clicks to pay). Distinct from siblings like create_booking or list_products.

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

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

Implied usage: use when creating a checkout for store products. Mentions no login required on agent side, but lacks explicit when-not-to-use or alternative tools.

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

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

No annotations are provided, so the description carries the full burden. It discloses the timezone behavior of slot times, which is valuable. However, it does not explicitly state that this is a read-only operation, nor mention any side effects, rate limits, or error conditions.

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

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

The description is two sentences with no wasted words. It front-loads the purpose in the first sentence and provides critical usage details in the second. Every sentence earns its place.

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

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

Given 3 parameters, no output schema, and no annotations, the description covers input usage well. It lacks details on return format or handling of unavailability, but the tool name implies a list of slots. Minor gap in output description.

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

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

Schema coverage is 100%, but the description adds meaning beyond the schema: it explains how to obtain serviceId and place_slug from a sibling tool, and reinforces the date format. This contextual usage guidance is valuable.

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

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

The description clearly states the verb (get) and resource (available time slots for a bookable service on a given date). It mentions serviceId from a sibling tool, helping differentiate from get_showtimes or similar, but does not explicitly distinguish from all siblings.

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

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

The description provides when-to-use guidance: 'pass serviceId from list_booking_services' and 'use the same place_slug'. It also includes a timezone caveat. However, it does not explicitly state when not to use or list alternatives like create_booking.

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

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

No annotations are provided, so the description must convey behavior. It accurately describes the return fields (ticket names, prices, sale status, quantity left) and implies a read-only operation with no side effects.

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

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

The description is two sentences, immediately stating the purpose and what it returns, without any superfluous words.

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

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

Given the absence of an output schema, the description effectively lists the key return fields. It does not cover error conditions or authentication, but for a simple GET tool, this is acceptable.

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

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

The parameter 'event_slug' is described both in schema and description with the same guidance to use from 'list_events'. Since schema coverage is 100%, the description adds minimal additional meaning beyond reinforcing the source tool.

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 retrieves ticket types and prices for a specific event from Wix Events. It clearly distinguishes from sibling tools like 'reserve_event_tickets' (which involves purchasing) and 'list_events' (which lists 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?

It instructs to pass the event slug from 'list_events', providing a clear prerequisite and usage context. It does not explicitly state when not to use, but the retrieval nature 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 of disclosing behavioral traits. The description only says what the tool returns; it does not mention side effects, required authentication, rate limits, or potential errors (e.g., if no loyalty program exists). This is insufficient for an AI agent to fully understand 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, concise sentence of about 20 words. It is front-loaded with the verb 'Get' and immediately states the resource. Every word adds value; no wasted 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?

Given that there are no parameters, no annotations, and no output schema, the description provides sufficient information about the return values (program name, points currency, tier structure). It is complete enough for a simple read operation, though it could mention error handling for missing loyalty programs.

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

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

The input schema has zero parameters, so the baseline is 4. The description does not need to add parameter information. However, it could be improved by noting that no parameters are required because it works on the current site context.

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

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

The description clearly states the tool's purpose: to get loyalty/rewards program details for the site. It specifies the exact outputs: program name, points currency name, and tier structure with required points per tier. This distinguishes it from sibling tools which cover bookings, events, menus, 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 does not explicitly state when to use this tool or when not to. It gives no context about prerequisites (e.g., site must have a loyalty program enabled). While it is implied that this tool is for retrieving loyalty info, it lacks guidance on alternatives 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 provided, so description carries full burden. It states 'Get full details' but does not disclose whether it is read-only, any rate limits, authentication requirements, or potential errors. The description lacks behavioral context beyond the action.

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

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

Single sentence, front-loaded with purpose, no wasted words. Efficient and to the point.

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

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

No output schema, so description should explain return values. It lists some fields ('opening hours, ratings, address, and neighborhood') but not all possible fields. Adequate for a simple tool but lacks completeness.

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

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

Schema coverage is 100% with a single parameter 'slug'. Description adds an example value 'cafe-example' which adds marginal value beyond the schema's description. Baseline of 3 is appropriate as no significant extra semantics are 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 uses specific verb 'Get' and resource 'full details for a specific place', lists key fields (opening hours, ratings, address, neighborhood), and clearly distinguishes from sibling tools like search_places which are for listing/searching.

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

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

Description implies usage when you have a URL slug, but does not explicitly state when to use vs alternatives (e.g., search_places). 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?

Without annotations, the description explains the return content (menus with sections, dishes, prices, dietary labels). It does not mention read-only nature or error handling, but the behavior is straightforward for a simple retrieval tool.

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

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

The description is three sentences covering purpose, return, and prerequisite. It is front-loaded, efficient, and 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?

For a single-parameter tool with no output schema, the description adequately covers what the tool does and how to use it. It could add details on error cases or output format, but overall 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 schema already describes the place_slug parameter. The description adds value by specifying how to obtain the slug (from search_places or list_categories), which 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 tool retrieves a restaurant's food menu with sections, dishes, descriptions, prices, and dietary labels. It specifies the resource (restaurant menus) and the action (get), distinguishing it from sibling tools like search_dishes or get_place.

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

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

The description explicitly instructs to use search_places or list_categories first to obtain the place_slug, providing clear prerequisite context. It could be improved by noting when not to use this tool (e.g., for cross-restaurant dish search), but the guidance is sufficient.

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

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

With no annotations, the description carries full burden. It discloses the returned fields and that only published reviews are included, but lacks details on ordering, pagination behavior, or any side effects (implicitly read-only).

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

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

Two sentences, no redundancy, front-loaded with purpose and output. 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 read tool with one optional parameter and no output schema, the description covers purpose, scope (published), and return format. No critical information is missing.

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

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

Schema coverage is 100% with one well-described parameter (limit). The description adds value by listing the return fields beyond the schema. Baseline 3 is met, and additional context justifies a 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 gets published reviews from Wix Reviews, specifying the exact fields returned (name, rating, title, content). This distinguishes it from sibling tools which are mostly for other resources or actions.

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

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

The description implies usage when reviews are needed, but does not explicitly state when to use this tool over alternatives. No exclusions or alternative names are given.

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

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

No annotations provided, so the description bears full burden. It explains the return structure (cinema, format, language) and a prerequisite, providing adequate behavioral context for a read-only query. No destructive or rate-limit info needed.

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 waste. The first sentence states purpose, the second details returns and requirements. Information is front-loaded and efficient.

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

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

For a simple query tool with 2 parameters, no output schema, and no annotations, the description is complete. It covers input, output, and prerequisites, enabling an agent to use the tool correctly in context with siblings.

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 covers both parameters with descriptions (100% coverage). The description adds value by linking movie_slug to list_movies and clarifying date default, enhancing semantic understanding beyond schema.

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

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

Description clearly states the verb 'Get', the resource 'showtimes', and the scope: specific movie, cinemas in this neighborhood, given date. This distinguishes it from sibling tools like list_movies 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?

While it mentions the prerequisite 'movies_enabled on this site', there is no explicit guidance on when to use this tool versus alternatives. The usage context is implied but not directly stated.

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 clearly indicates this is a read-only information retrieval (no mention of mutations), and since no annotations are provided, it adequately sets expectations about 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?

Two sentences efficiently convey all necessary information without redundancy, front-loading the core purpose.

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 informational tool with no parameters and no output schema, the description provides all relevant context: what data to expect and usage scenarios.

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

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

No parameters exist, so the description correctly adds no parameter-level detail beyond what the schema (empty) provides, 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 explicitly states it returns basic site info plus local time and weather, making the purpose crystal clear and distinct from sibling tools like get_place that focus on specific 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?

It explicitly advises using this tool for time/weather queries, providing clear usage context; however, it does not explicitly mention when not to use it 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?

The description mentions 'recent published' and lists return fields, but no annotations are present. It does not disclose ordering, pagination, or authentication requirements. Adequate for a simple read tool.

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

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

The description is a single sentence that efficiently conveys the tool's purpose and return fields, with no unnecessary words.

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

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

Given the tool's simplicity, the description covers the key aspects: what it retrieves, the source (Wix Blog), and return fields. It lacks output schema but compensates by listing fields.

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

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

Schema coverage is 100% with descriptions for both parameters. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states it lists recent published blog posts for the Wix Blog, and specifies the return fields. It distinguishes itself from sibling tools like list_categories by focusing on 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?

No explicit when-to-use or when-not-to-use guidance is given. The purpose is clear, but alternatives are not mentioned, leaving the agent to infer from sibling names.

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

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

With no annotations, the description fully discloses behavioral traits: it lists services for EVERY venue (including those without online booking), explains that bookableViaMcp indicates booking availability, and that id is null when not bookable. It also clarifies that only the version with place_slug works with create_booking.

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

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

The description is well-structured, starting with the core purpose then detailing behavior, edge cases, and return fields. It is comprehensive but slightly lengthy; however, every sentence adds value. Could be slightly more terse but still excellent.

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 lists returned fields (name, description, price, duration, bookableViaMcp) and explains the null id case. It integrates well with sibling tools and provides complete 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 single parameter place_slug is fully documented in the schema, but the description adds significant value: it specifies that the slug comes from search_places, explains the two modes of operation, and strongly recommends its use. This goes well beyond the schema's description.

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

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

The description clearly states the tool lists a venue's services with price and duration. It distinguishes from siblings like search_places and create_booking by explaining the relationship. It explicitly covers both modes (with and without place_slug), leaving no ambiguity.

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

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

The description provides explicit guidance: use place_slug (from search_places) for venue services 'in almost every case', and explains the rare alternative. It also advises what to do when bookableViaMcp is false, directing the agent to bookingUrl or venue page.

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 accurately describes the read-only behavior of returning a taxonomy. It adds context on output structure (labels, types, counts), but does not mention authentication needs or rate limits. Still, for a simple retrieval, it is sufficiently 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 a single concise sentence that front-loads the main action and lists specific output components. No wasted words.

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

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

Given the tool has no parameters and no output schema, the description is fairly complete, specifying the taxonomy contents. It could mention site specificity or any implicit constraints, but overall it is adequate.

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

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

Input schema has zero parameters with 100% coverage ; the description adds no parameter details, which is acceptable as there are none. 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 returns the full category taxonomy, enumerating specific contents: top-level groups, subcategories, localized labels, schema.org types, and live place counts. It distinguishes itself from sibling list tools by specifying its unique 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?

The description implies usage for retrieving the category taxonomy but provides no explicit guidance on when to use this tool versus alternatives like list_products or search_places. No when-not or context for exclusion 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 the weather forecast inclusion for near-term events and live resolution for 'agora' filter. Does not mention auth, rate limits, or destructive side effects, but covers key 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 concise sentences that front-load the core purpose and then add key details. No wasted words; every sentence earns its place.

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

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

With only 3 simple params and no output schema, the description sufficiently covers use cases and special filter behavior. Minor gap: does not specify return format beyond listing fields, but sufficient for size.

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 significant value by explaining the purpose of filter values (e.g., 'agora' live resolution) which goes beyond schema descriptions. The limit and upcoming_only params are already well-described in schema.

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

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

The description clearly states it lists upcoming events with date, venue, price, URL, and includes extra behavior for events within 7 days. This uniquely distinguishes it from sibling 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?

Explicit guidance on using the 'filter' parameter, especially 'agora' for live results, and contrasts with cached pages. However, it does not explicitly mention when to use alternatives 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 carries the full burden. It states that the tool retrieves all FAQs and groups them by category, implying a read-only operation. While it doesn't discuss authentication, rate limits, or edge cases like empty results, the behavior is straightforward and adequately disclosed for a simple retrieval tool.

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

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

The description is two sentences, front-loaded with the main purpose, then usage guidance. Every word adds value, with no redundancy or unnecessary 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?

Despite having no output schema, the description explains what the tool returns (FAQs grouped by category) and when to use it. For a simple, parameterless retrieval tool, this is complete and 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?

The tool has zero parameters, and schema description coverage is 100%. Per guidelines, baseline for 0 parameters is 4. The description does not add parameter semantics beyond the schema, which is acceptable since there are none.

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

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

The description clearly states the tool retrieves all FAQ questions and answers for the site, grouped by category, using the verb 'Get' and specific resource 'FAQ questions and answers'. It distinguishes from siblings by focusing on FAQs, which is unique among a list of siblings mostly related to bookings, menus, 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 explicitly says 'Use this to answer common questions about the site — opening hours, parking, policies, etc.' This provides clear guidance on when to use the tool. It doesn't explicitly state when not to use it, but the context of sibling tools implies alternatives for other queries.

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

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

No annotations are provided, so the description must carry the full burden. It states the output briefly but does not explicitly mention that the tool is read-only or has no side effects. However, as a listing tool, the description implies safety.

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

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

Two short sentences with no filler. The purpose is stated immediately, and the usage guideline is efficiently conveyed.

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

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

Given no parameters and no output schema, the description adequately explains the tool's return value and its role relative to submit_form. However, it could clarify if all forms or only certain types are listed.

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

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

The tool has no parameters, and the schema coverage is 100%. The description adds value by explaining what the returned data contains, earning a baseline of 4.

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

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

The description clearly states the tool lists available contact/signup forms, specifying the resource ('Wix Forms') and the returned data (name, ID, field definitions). It distinguishes itself from the sibling 'submit_form' by indicating it's a prerequisite.

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

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

Explicitly says 'Use before submit_form to discover which fields to fill,' providing clear guidance on when to use this tool relative to a specific sibling tool.

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

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

No annotations provided, so description carries full burden. Only states it lists guides with editorial notes; lacks details on whether results are paginated, sorted, authenticated, or any side effects. Minimal behavioral disclosure.

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

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

Two concise sentences, no redundant information, front-loaded with the primary purpose.

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

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

With no output schema, description could elaborate on return format or fields (e.g., what the editorial notes contain). However, the tool is simple (one param, no nested objects), so overall it is adequate but not fully complete.

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

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

Schema description covers 100% of the single parameter (limit) with details on default and max. Description adds no additional meaning beyond the schema, so baseline score of 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?

Description clearly states verb 'list' and resource 'curated editorial guides', distinguishes from sibling tools like list_blog_posts by specifying 'ranked places with editorial notes' and targeting 'best X in this neighborhood' 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?

Explicitly says it is the best source for 'best X in this neighborhood' questions, providing clear context for use. Does not explicitly mention when not to use or list alternatives, but context is sufficient.

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

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

No annotations provided, so the description bears full burden. It discloses that the tool returns data scoped to neighborhoods, includes categories, and lists returned fields. This is sufficiently transparent for a read operation.

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

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

Three concise sentences: first sets scope, second summarizes returns, third lists fields. Front-loaded with key constraint. 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?

Without an output schema, the description adequately lists returned fields (title, genres, TMDB rating, runtime, URL). It also explains filter meanings and availability constraint. Lacks mention of sorting or pagination beyond limit, but this is acceptable.

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

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

Schema coverage is 100%, but the description adds extra context: e.g., 'coming_soon' = unreleased or not playing locally, 'streaming' = available on streaming services in Brazil. This adds meaning 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 uses a specific verb ('List') and resource ('movies'), and clearly distinguishes the categories (now-showing, coming-soon, streaming). It sets the tool apart from siblings like 'list_events' or 'get_showtimes' by focusing on movie catalog with specific filters.

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 each status filter. However, it does not explicitly state when to avoid this tool or mention alternatives like 'get_showtimes' for specific showtimes.

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 must cover behavior. Mentions FLASH countdown but not read-only nature, sorting, pagination, or definition of 'active'. Minimal disclosure beyond basic operation.

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

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

Two sentences, first states core action, second lists specific fields and special case (FLASH). Efficient, front-loaded, 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 simple tool with 2 params and no output schema, description lists return fields and a special offer type. Missing definition of 'active' and default sorting, but suffices for basic understanding.

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 100%, baseline 3. Description adds nuance for kind enum ('FLASH offers have a countdown deadline') but doesn't extend meaning for limit or kind beyond schema. Marginal value.

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

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

Description clearly states verb 'list' and resource 'active promotions and deals' with specific return fields (discount label, promo code, CTA link, validity window, business). Distinguishes FLASH offers with countdown, differentiating from other list tools in siblings.

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

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

Implied usage for retrieving deals but lacks explicit when-to-use, when-not-to-use, or alternatives. No mention of prerequisites or context for choosing over other tools like list_products or list_events.

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 beyond the implied read operation (e.g., auth requirements, rate limits, or side effects). It does specify the return fields, but lacks explicit safety 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 a single, front-loaded sentence with no unnecessary words, clearly stating the action 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?

Given no parameters and no output schema, the description sufficiently explains what the tool returns and contextualizes it as site-specific. It lacks pagination or filtering details, but those are not needed with zero parameters.

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 is empty, so schema description coverage is 100%. The description does not need to explain parameters, and it adds no extra semantic value beyond the schema.

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

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

The description clearly states it lists membership/subscription plans with specific return fields, and explicitly refers to 'Wix Pricing Plans' which distinguishes it from other list tools like list_products or list_offers.

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

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

The description implies usage for retrieving pricing plans but does not provide explicit guidance on when to use it over alternatives, nor does it mention when not to use it.

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

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

With no annotations, the description carries the full burden. It accurately describes a read operation listing products but does not mention pagination behavior (beyond limit), authentication needs, or rate limits. Provides basic transparency 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?

Single sentence with front-loaded purpose and includes key return fields. No wasted words; every phrase 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?

The description explains return values (name, price, stock status, product type) despite no output schema. However, it lacks details on pagination, sorting, or default ordering, which would improve completeness.

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

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

Schema coverage is 100% with clear descriptions for both parameters (q and limit). The description adds no new information about parameters beyond what the schema already 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 clearly states the tool lists products from Wix Stores, specifies the returned fields (name, price, stock status, product type), and naturally distinguishes from sibling tools like list_blog_posts or list_events.

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

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

No explicit guidance on when to use this tool versus alternatives. Usage is implied by the domain (Wix Stores products), but no when-not-to-use or prerequisite 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?

No annotations are provided, so the description carries the full burden. It discloses the return fields (name, profile URL, category, metadata) but does not explicitly state the tool is read-only or discuss any side effects, rate limits, or auth needs.

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 and examples, followed by return fields. No wasted words or redundancy.

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

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

Given no output schema, the description lists return fields, which compensates. For a simple list with one optional parameter, it is fairly complete but could mention default limit or pagination.

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

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

Schema coverage is 100% (the 'limit' parameter has a description in the schema). The tool description adds no additional parameter-specific meaning beyond what the schema already provides, hence baseline score of 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 lists 'solo service-provider profiles' and specifies they are businesses without a fixed physical location, with examples. This distinguishes it from other list_* sibling tools like list_products or list_booking_services.

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

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

The description provides clear context on what tool lists (solo, no physical location) but does not explicitly state when to use versus alternatives or when not to use it.

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

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

No annotations provided, but the description fully discloses the critical behavior: the restaurant is not notified until confirmation link is clicked, email expires in 24 hours, and the link is not returned to the agent. Uses all-caps warning for emphasis.

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

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

Concise yet comprehensive. Each sentence adds value, front-loaded with the critical point about the restaurant not being notified. 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 provided, yet description does not specify what the tool returns (e.g., request ID). While behavioral context is thorough, the lack of return value details creates a gap for the agent.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds context about using a real email but does not significantly enhance parameter meaning beyond the schema. Adequate but not exceptional.

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 'Request a table at a restaurant' and distinguishes from siblings like create_booking by emphasizing this is a request, not a confirmed booking. Specific verb and resource with explicit scope.

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 explains the two-step confirmation process, tells the agent to inform the user to check their inbox, and clarifies that the restaurant confirms out of band, guiding when to use this vs. other 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?

Discloses critical behavioral details beyond annotations: hold is temporary, nothing is paid until checkout, hold expires automatically. No annotations provided, so description fully covers behavioral expectations.

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

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

Three sentences, each essential. First sentence states purpose and outcome, second highlights the critical caveat, third provides limits and exclusion. 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 explains return (checkout URL) and lifecycle. For a reservation tool, it covers purpose, constraints, and behavior adequately.

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

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

Schema coverage is 100% (both parameters described in schema). Description adds additional constraints (max 10 tickets per reservation, max 10 ticket types) not present in schema, enhancing clarity.

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 ('Hold tickets'), the resource ('event sold through this site'), and the result ('return a checkout URL'). It distinguishes from sibling tools by specifying it's for Wix Events only.

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

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

Explicitly provides when to use (events sold directly), when not (external events), and constraints (max 10 tickets and 10 ticket types, hold is temporary). The instruction to use the event's own ticketUrl for external events gives clear direction.

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 async nature (email confirmation), expiration, and that the link is not returned. Warns about using a real address. No annotations exist, so description carries full burden and meets it well.

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

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

Single paragraph, front-loaded with purpose, then behavior, then instructions. 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?

Covers main behavioral aspects but does not describe return value. With no output schema, a brief note on what the tool returns would improve completeness. Otherwise, sufficient for an RSVP 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 minimal value beyond schema (e.g., source of event_slug). Does not significantly enhance 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 verb 'RSVP' and resource 'event' with context 'Wix Events'. Distinguishes from sibling tools like create_booking or request_reservation.

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

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

Explicitly instructs when to use (free events), what to expect (confirmation email, no guest list), and what not to do (deliberately not returning link). Provides actionable steps for the agent.

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

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

With no annotations provided, the description fully explains the tool's behavior: grouping by dish, returning price, description, dietary labels, and place URL. It also covers the default behavior when query is omitted. While it doesn't mention permissions or rate limits, the search nature makes those less 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?

The description is two sentences long, front-loaded with the core purpose, and every part adds value. 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?

Despite lacking an output schema, the description fully explains the return values (price, description, labels, URL) and covers both use cases (with query and without). It is complete for a search tool of this 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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the effect of omitting the query parameter (returning top dishes) and providing real-world examples. This goes beyond the schema's basic descriptions.

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

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

The description clearly states the tool's purpose: finding restaurants that serve a specific dish in a neighborhood, searching across all menu items and grouping by dish. It provides concrete examples (e.g., 'feijoada') and distinguishes itself from sibling tools like search_places by focusing on dish-level 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 explicitly tells when to use the tool ('where can I eat X' questions) and the behavior when omitting the query (list top dishes). However, it does not mention when not to use it or point to alternatives like get_restaurant_menus or search_places, which could be helpful for users wanting restaurant-level information.

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

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

No annotations are provided, so the description carries the full burden. It discloses that q is accent-insensitive and typo-tolerant, and that opening hours are returned in Google Maps periods format. These are useful behavioral traits beyond 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?

The description is three sentences: purpose, q behavior, and filtering/output format. It is concise but the phrase 'in this neighborhood' in the first sentence might imply the neighborhood parameter is required when it is optional, slightly reducing clarity.

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

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

Given 4 optional parameters, no output schema, and many siblings, the description covers search behavior, filtering, and opening hours format. However, it omits default limit (20) and other output details like ordering by relevance, making it adequate but not comprehensive.

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. The description adds examples for q ('acai' finds 'Açaí') and clarifies the optional filtering for category and neighborhood, but does not add substantial new semantics 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 clearly states 'Search for places (restaurants, cafes, shops, etc.) in this neighborhood.' The verb 'search' and resource 'places' are specific. The tool is distinguished from siblings like get_place or list_guides by targeting neighborhood-based place discovery.

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 (searching for places with optional filters) but does not explicitly state when not to use or suggest alternatives. Given siblings like get_place for a specific place or list_guides for guides, no exclusion guidance is provided.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a 'submissionId on success' and implies mutation by 'submit'. However, it does not detail authentication, error handling, or side effects.

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

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

The description is two sentences with no fluff, front-loading the action and prerequisite. Every sentence adds value.

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

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

Given 2 parameters, a prerequisite call, and a return value, the description covers essential usage. No output schema exists, so mentioning the return value is helpful. Minor omissions like error scenarios are acceptable for this 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?

Schema description coverage is 100%, with both parameters having descriptions. The description adds context by explaining the example format for 'fields' and that 'formId' comes from list_forms, but this is minimal extra value beyond the schema.

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

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

The description clearly states the verb 'Submit' and the resource 'form' with context 'Wix Forms'. It also distinguishes from sibling tools by mentioning the prerequisite to call list_forms first, avoiding confusion.

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

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

The description explicitly instructs to 'Call list_forms first to get the formId and field keys', providing clear guidance on how to use this tool. While it doesn't state when not to use it, the prerequisite is well-defined.

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