Agenda SP

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

No annotations are provided, so the description fully informs about key behaviors: returns checkout URL, booking stays off calendar until payment, slot re-validation server-side, email not verified. All critical traits disclosed.

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

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

Three sentences with no waste. The warning is front-loaded with caps for emphasis. Each 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?

No output schema exists, but the description explains the return (checkout URL) and post-conditions. Pre-conditions (call get_availability) and limitations (email not verified) are clear. Complete for a mutation tool with nested objects.

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%, describing all parameters. The description adds context about using exact ISO instants from get_availability and that contact fields are required, but does not add extensive meaning beyond the 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 it books an appointment slot at a venue, distinguishing it from siblings like get_availability or request_reservation. The verb 'Book' and resource 'appointment slot' are specific.

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

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

Explicitly instructs to call get_availability immediately before, warns that nothing is booked until payment (user must open link), and notes that contact email is not verified. Provides clear usage context.

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

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

With no annotations, the description carries the full burden. It mentions that the user clicks the URL to complete payment and that no login is required, which are helpful behavioral hints. However, it does not disclose whether the action creates any server-side state, if the URL expires, or what happens on the backend, leaving room for improvement.

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, no wasted words. The first sentence front-loads the purpose and resource, the second provides a key usage detail. 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?

Given the tool's simplicity (one parameter, no output schema), the description covers the core functionality and a key constraint. It could be slightly more complete by explicitly stating that the tool returns a URL, but overall it is sufficient for an agent to understand the tool's role.

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 schema has 100% coverage with descriptions, so the description adds moderate value beyond the schema. It clarifies that the items are products and that the result is a payment URL, but does not elaborate on the structure or format of the IDs or quantities.

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 ('Create a direct checkout URL'), the resource ('one or more store products'), and the context ('Wix Stores'). It distinguishes itself from siblings like create_booking, which focuses on bookings, not store products.

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

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

The description explains when to use this tool (creating a checkout URL for store products) and notes that no login is required on the AI agent side, implying ease of use. However, it does not explicitly state when not to use it or list 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 provided, but description adds value by disclosing that slot times are returned in the venue's timezone. Lacks details on error cases or idempotency, but adequate given simplicity.

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

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

Two sentences plus a short note, all front-loaded. Every sentence adds value with no wasted words.

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

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

No output schema, but description covers key usage flow and timezone behavior. Lacks detail on return format (e.g., list of time strings), but sufficient for a simple availability check.

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 context: serviceId and place_slug should be from list_booking_services, and date format is specified. Adds meaning beyond schema.

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

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

Description states 'Get available time slots for a bookable service on a given date' with specific verb and resource, clearly distinguishing from sibling tools like list_booking_services and create_booking.

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

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

Explicitly tells when to use: pass serviceId from list_booking_services and date in YYYY-MM-DD, and reuse place_slug. Mentions timezone nuance. Does not explicitly list 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 are provided, so the description must disclose behavior. It clearly states the return values (ticket names, prices, sale status, quantity left), indicating a read-only operation with no destructive 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 efficiently cover purpose, usage, and output, with no redundant information.

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

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

For a simple read operation with one parameter and explicit output description, the description is fully complete. The lack of an output schema is compensated by listing return fields.

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

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

The only parameter, event_slug, is described in both the schema and the description as 'Event slug from list_events.' Since schema coverage is 100%, the description adds no new meaning, meeting the baseline 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 retrieves ticket types and prices for a specific event, distinguishing it from sibling tools like list_events (which lists events) and reserve_event_tickets (which reserves 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?

It explicitly instructs to pass the event slug from list_events, indicating a prerequisite and data flow. While it does not list when not to use or alternatives, the context from siblings implies this is for pre-reservation info retrieval.

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

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

No annotations exist, so the description carries full burden. It honestly lists return fields but does not explicitly state read-only behavior or any side effects. For a get tool, 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?

A single, concise sentence that front-loads the action and immediately specifies return details. No filler 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?

For a parameterless tool, the description is complete in explaining what it returns. However, lack of output schema means the description must fully describe return, which it does adequately but could mention site-specific context.

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

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

No parameters exist, baseline is 4. The description adds value by detailing the return content (program name, points currency, tier structure), which is beyond the empty 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 retrieves loyalty/rewards program details, specifying the exact resource and verb. It distinguishes from siblings like 'get_place' or 'get_event_tickets' by focusing on loyalty information.

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

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

The description implies use when needing loyalty info for the current site but does not provide explicit guidance on when to use this tool versus alternatives. No exclusions or conditions are mentioned.

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

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

With no annotations, the description carries full burden. It discloses the returned fields but does not mention behavioral aspects such as read-only nature, potential errors (e.g., invalid slug), or performance characteristics. It is adequate but not highly 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, well-structured sentence that conveys all necessary information without redundancy or unnecessary detail.

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

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

Given there is no output schema, the description provides a good overview of the return content (opening hours, ratings, address, neighborhood). It is largely complete for a retrieval tool, though it could mention error handling for non-existent slugs.

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

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

The schema has 100% coverage for the single parameter 'slug', and the description adds meaning beyond the schema by explaining that it takes the URL slug and providing an example, as well as stating what the tool returns, which aids correct invocation.

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

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

The description clearly states the verb 'get' and the resource 'full details for a specific place', and lists included fields like opening hours, ratings, address, and neighborhood, distinguishing it from the sibling 'search_places' which is for searching/filtering places.

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

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

The description indicates when to use the tool (when you have a URL slug and need full details), but does not explicitly state when not to use it or mention alternatives like 'search_places' for cases without a slug. However, the sibling list implies the distinction.

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 clearly states what the tool does and what data it returns (menus with sections, dishes, labels). It implies a read operation, though not explicitly marked safe. Lacks details on permissions or error behavior, but sufficient for its simplicity.

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

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

Two sentences that front-load the core purpose and efficiently convey all necessary information without superfluous content. Every sentence adds value.

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

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

For a simple tool with one parameter and no output schema, the description covers purpose, parameter source, and return content. Could mention that it returns all menus or any error conditions, but overall adequate.

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

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

The schema already describes the place_slug parameter (100% coverage), and the description adds valuable context: an example ('bar-do-ze') and its origin (from search_places or a place URL), significantly aiding correct invocation.

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

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

The description uses a specific verb ('Get') and resource ('food menu for a specific restaurant'), and lists the returned data (sections, dishes, descriptions, prices, dietary labels), clearly distinguishing it from sibling tools like search_dishes.

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

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

Provides explicit guidance to use search_places or list_categories first to obtain the required place_slug, helping the agent avoid misuse. Could be improved by specifying when not to use this tool (e.g., for other types of content).

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 must cover behavioral traits. It implies read-only behavior via 'Get published reviews' and mentions return fields, but omits details like pagination defaults, sorting, or authentication requirements. This is adequate for a simple tool but leaves some 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 a single, clear sentence that efficiently conveys the tool's purpose and output. No unnecessary words or repetition.

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

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

Given the simple tool (one optional parameter, no output schema), the description adequately lists returned fields and the resource. However, it could mention default limit or ordering to be fully self-contained without relying on schema.

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

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

Schema coverage is 100% (one parameter, 'limit', fully described in schema). The description does not add any additional information about parameters; it merely restates the tool's action. Baseline 3 is appropriate as the schema already provides sufficient parameter meaning.

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

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

The description clearly states the tool retrieves published reviews for a specific resource (Wix Reviews) and lists the returned fields (reviewer name, rating, title, content). It distinctly separates this tool from sibling tools that handle bookings, events, products, 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, such as when pagination or filtering by product is needed. No when-to-use or when-not-to-use context 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, so the description carries full burden. It correctly states a prerequisite (movies_enabled) and implies the tool is read-only (get). It does not mention authentication, rate limits, or pagination, but these are acceptable for a simple lookup tool. The description is adequate but not rich.

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: two sentences covering purpose, output, and a prerequisite. No redundant information; every part is essential.

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

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

Given two parameters with full schema coverage and no output schema, the description is mostly complete. It explains the return structure (cinema, times, format, language) and a prerequisite. The phrase 'in this neighborhood' is slightly ambiguous but understandable in context. A more detailed explanation of the neighborhood scope 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 description coverage is 100% for both parameters (date and movie_slug), so the schema already explains them well. The description adds minimal extra meaning: it mentions the default for date (today) and that movie_slug comes from list_movies. This provides marginal additional value, meeting the baseline.

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

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

The description clearly states the tool's purpose: get showtimes for a specific movie at cinemas in the neighborhood for a given date. It specifies the output includes cinema, session times, format, and language, distinguishing it from siblings like list_movies (which lists movies).

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: it is used to retrieve showtimes for a specific movie on a specific date, and it requires movies_enabled on the site. It implies a dependency on list_movies for the slug. However, it does not explicitly state when to use this tool versus alternatives like get_availability, but the use case is well-defined.

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

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

Since no annotations are provided, the description carries full burden. It describes the output (read-only info) and adds context like local time and weather. It does not mention rate limits or caching, but for a simple info endpoint, this is adequate.

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

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

Two sentences, front-loaded with the return value list and a clear usage directive. Every word earns its place; no 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?

With zero parameters, no output schema, and a simple purpose, the description fully informs the agent about what to expect 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?

Schema coverage is 100% as there are no parameters. Description adds no parameter details, but none are needed. 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 uses the specific verb 'Returns' and clearly identifies the resource as 'basic information about this neighborhood directory', listing specific data fields. It is distinct from all sibling tools which focus on other domains like bookings, menus, 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 provides usage context: 'Use this for any "what time is it there" or "what's the weather like" context.' This gives clear guidance on when to select this tool over alternatives.

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

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

No annotations are provided, so the description carries the burden. It mentions 'recent' and 'published', implying filtering, and lists return fields. However, it does not disclose auth requirements, rate limits, or side effects (though none expected). Adequate but not comprehensive.

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

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

The description is a single sentence that is front-loaded with the action and resource. Every word adds value, with no wasted space.

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 fields, and the schema covers the optional parameters. For a simple list tool, this is fairly complete. It could mention pagination behavior (e.g., 'default 10, max 50' is in schema but not description), but overall sufficient.

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

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

Schema description coverage is 100%, with both parameters already described in the schema. The tool description adds no additional meaning beyond what is in 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 the verb 'List' and the resource 'recent published blog posts' for the specific site. It also enumerates returned fields, distinguishing it from sibling list tools like list_events 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?

No guidance is provided on when to use this tool versus alternatives. Sibling tools include many other 'list_*' operations, but no criteria for selecting this one over others 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?

With no annotations, the description fully discloses key behaviors: it lists services for all venues regardless of online booking capability, and explains how to interpret bookableViaMcp to know if booking is possible via create_booking. It also describes the return fields, adding transparency beyond a simple list.

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 informative but slightly verbose, containing some redundant phrasing like 'that is what you want in almost every case.' However, it is well-structured, front-loads the main purpose, and each sentence adds value without being overly long.

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 return values (name, description, price, duration, bookableViaMcp) and handles edge cases (null id, non-bookable venues). It also provides integration context with create_booking, making it complete for an agent to decide when and how to use 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?

The schema already describes the parameter with 100% coverage, including a strong recommendation. The tool description reinforces this by explaining the two modes of operation (with and without place_slug), adding contextual value beyond the schema's description of the parameter itself.

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 between listing services for a specific venue (using place_slug) and listing the directory's own services, which is a crucial differentiation. The verb 'list' and resource are specific.

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

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

Explicitly advises to pass place_slug in almost every case, noting that only this form integrates with create_booking. It warns against omitting place_slug by explaining the alternative yields directory services, which most sites lack. This provides clear when-to-use guidance.

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

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

With no annotations, the description discloses the expected read-only behavior and the data returned. While it does not mention potential limitations like data size or update frequency, the description is straightforward and provides sufficient transparency for a simple list operation.

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

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

A single sentence that immediately conveys the tool's purpose and output structure. No unnecessary words or repetition.

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

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

Given the lack of parameters and output schema, the description is thorough in explaining what the tool returns (top-level groups, subcategories, labels, types, counts). It covers the essential information for an agent to understand the tool's output.

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 schema coverage is 100%. Per guidelines, a baseline of 4 is appropriate since no parameter description is needed, and the description adds no confusion.

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 returns the full category taxonomy, specifying the exact components: top-level groups, subcategories, localized labels, schema.org types, and live place counts. It distinguishes from sibling list_* tools by focusing on the category taxonomy of the directory site.

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

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

No guidance on when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or comparisons with other list_ tools, leaving the agent to infer the appropriate context.

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

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

Despite no annotations, the description adds key behavioral context: 'agora' filter is resolved live on each call, and weather forecast is included for next-7-day events. 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?

Three sentences, front-loaded with core purpose, each sentence adds unique value. No wasted words.

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

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

Describes return fields clearly, includes optional weather behavior. No output schema, but coverage is adequate for a list tool with simple returns.

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), but the description adds substantial semantics: explains each filter enum value in detail, including exclusions for season runs and day-granular sources, and clarifies the weather forecast inclusion.

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

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

The description clearly states it lists upcoming events with specific fields. It distinguishes from siblings like 'get_event_tickets' and 'get_showtimes' by focusing on event listing with date, venue, price, and URL, but does not explicitly differentiate.

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 detailed guidance on how to use the 'filter' parameter with examples like 'agora' for live events. Lacks explicit when-not-to-use vs alternatives, but the filter explanations effectively guide selection.

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

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

Without annotations, the description carries full burden; it accurately describes the read operation and grouped nature, though it could mention default behavior if no FAQs exist.

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

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

Two concise sentences efficiently convey purpose and usage, with no extraneous 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 parameterless tool with no output schema, the description sufficiently covers purpose and usage context, fitting well among sibling tools.

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

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

With zero parameters and 100% schema coverage, the description adds no parameter info, which is acceptable as there is nothing to add.

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 all FAQ questions and answers for the site, grouped by category, distinguishing it from siblings like 'get_site_info' or 'list_forms'.

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 says to use it to answer common questions, implying usage, but does not explicitly mention when not to use or 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 full burden. It describes the operation as a read/list and details output contents. It could mention non-destructiveness, but the description is sufficient and doesn't contradict any 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 and output details. No wasted words.

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

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

For a simple list tool with no params and no output schema, the description fully covers what the tool does and how to use it in context.

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

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

Input schema has no parameters (schema coverage 100%), so description need not explain params. It adds value by describing the response structure (name, ID, field definitions), which aids the agent in understanding usage.

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

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

The description clearly states it lists available contact/signup forms (Wix Forms) and specifies returned data (name, ID, field definitions). This distinguishes it from siblings like submit_form.

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

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

Explicitly says 'Use before submit_form to discover which fields to fill,' providing clear when-to-use guidance and referencing an alternative tool.

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

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

No annotations are provided, and the description does not disclose any behavioral traits such as read-only nature, permissions, or side effects. For a listing operation, basic transparency about safety would be expected.

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

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

The description is extremely concise with two sentences. The first sentence defines the tool's purpose, and the second adds a use-case hint. 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 has only one optional parameter, no output schema, and no annotations, the description adequately covers what the tool does and suggests its best use case. However, it could mention what information the guides include or the ordering.

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

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

Schema description coverage is 100% for the single parameter 'limit,' with the schema already describing its behavior. The description adds no additional 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 the verb 'List' and the resource 'curated editorial guides' with specific detail about being 'best of' lists with editorial notes, distinguishing it from sibling tools like list_blog_posts 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?

The description explicitly states the tool is 'The best source for "best X in this neighborhood" questions,' providing clear context for when to use it. However, it does not mention when not to use it or provide 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?

Description lists returned fields (title, genres, rating, runtime, detail URL) and status filters, which is helpful. However, no annotations exist, and the description does not mention authentication, rate limits, side effects, or pagination behavior beyond the limit parameter.

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

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

Two sentences: first sets purpose and constraint, second lists output and filters. No wasted words, efficiently conveys all necessary 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?

Without an output schema, the description adequately describes return fields. It covers the main use case (listing movies) and parameters. Missing minor details like sorting default or pagination handling, but limit parameter covers part of that. Overall sufficient for the tool's complexity.

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

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

Schema coverage is 100% with clear descriptions. The description adds value by explaining what each status filter means in terms of local availability (e.g., 'now_showing = films with upcoming showtimes at local cinemas'), going beyond the schema's enum labels.

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

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

Purpose is crystal clear: listing movies with specific categories (now-showing, coming-soon, streaming). The verb 'list' and resource 'movies' are explicit, and the description distinguishes it from sibling list tools (e.g., list_events, list_products) by focusing on movies and local availability.

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

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

Context is clear: use when you need movies available in a neighborhood, with a constraint 'only on sites with movies_enabled'. No explicit alternatives or when-not-to-use, but the sibling list tools are for other entity types, so usage is implied.

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

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

No annotations are provided, so the description must disclose behavioral traits. It mentions return fields and notes FLASH offers have a countdown deadline, but does not cover auth requirements, rate limits, pagination details, or absence of side effects. Adequate for a simple read-only list tool but could be more 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?

Three sentences, purpose is front-loaded, no redundant or filler content. Every sentence contributes to understanding the tool's functionality 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?

Despite no output schema, the description clearly lists the returned fields (discount label, promo code, CTA link, validity window, business/place). With only two optional parameters, the tool is simple and the description covers all necessary information without 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% for both parameters, but the description adds value by explaining that FLASH offers have a countdown deadline, enriching the meaning of the kind parameter. The limit parameter is not elaborated beyond schema, but the extra context for kind justifies above-baseline 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?

Description clearly states it lists active promotions and deals in a neighborhood directory, distinguishing it from sibling list tools like list_blog_posts or list_products. The verb 'list' and specific resource 'promotions and deals' make purpose unambiguous.

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

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

The description implies usage for browsing available deals but does not explicitly state when not to use it or mention alternatives among siblings. However, the mention of kind filter (STANDARD vs FLASH) provides some contextual guidance for narrowing down offers.

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

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

No annotations are provided, so the description carries the burden. It clearly indicates this is a read-only list operation with no destructive effects, though it does not explicitly state that it is safe. The description is adequate for a simple query tool.

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

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

The description is a single concise sentence that efficiently conveys the tool's purpose and return data without 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 absence of parameters and output schema, the description is fully self-contained. It covers what the tool does and what it returns, leaving no ambiguity for a list operation.

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 beyond the empty schema by explaining what the returned data contains.

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 or subscription plans, specifies the site (Wix Pricing Plans), and enumerates the return fields (name, price, billing cycle, perks, direct checkout URL). This distinguishes it from sibling tools like list_products or list_blog_posts.

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

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

The description implies when to use this tool (to retrieve pricing plans) but does not explicitly state when not to use it or mention alternatives. However, the tool name and context make the usage fairly clear.

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

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

With no annotations provided, the description carries full behavioral disclosure burden. It only states what is returned, with no mention of side effects, authentication needs, rate limits, pagination behavior, or scope (e.g., site-level). The description is insufficient for a mutation-free read tool, though there is no contradiction.

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 purpose and return information without any wasted words, making it ideally concise for an AI agent.

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

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

For a simple list tool with complete schema coverage and no output schema, the description adequately covers purpose and return fields. However, it lacks details about scope (e.g., single site store) and fails to address usage guidelines or behavioral traits, making it minimally complete.

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

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

Schema coverage is 100% with both parameters described (q as search term, limit with defaults). The description does not add any additional meaning beyond the schema, meeting the baseline for high coverage.

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

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

The description explicitly states 'List products in this site's store (Wix Stores)' with a specific verb and resource, and lists return fields (name, price, stock status, product type), clearly distinguishing it from sibling list 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 guidance is provided on when to use this tool versus alternatives (e.g., other list_* tools), nor are there any exclusionary or prerequisite conditions. The usage context is entirely implied by the resource name.

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

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

No annotations are provided, so the description carries full burden. It lists output fields (name, URL, category, metadata) but does not explicitly state that the operation is read-only or disclose any other behavioral traits beyond the output.

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

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

Two efficient sentences that define purpose and output without any extraneous information. Front-loaded with clear examples, 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?

For a simple list tool with one optional parameter, the description adequately explains the resource and output. Lacks mention of pagination or sorting but is otherwise complete given the low 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% for the single parameter 'limit', which already has a description. The tool description adds no additional parameter semantics beyond the schema, so baseline score of 3 is appropriate.

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

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

The description uses a specific verb 'list' and resource 'solo service-provider profiles', with clear examples (dog walkers, tutors) that distinguish it clearly from sibling tools like list_events 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?

No explicit guidance on when to use this tool versus alternatives. The description describes what it does but does not state when it is appropriate or inappropriate to use, nor does it mention prerequisites or exclusions.

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

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

No annotations are provided, so the description carries full weight. It fully discloses the asynchronous behavior: the request is held, a confirmation email is sent, the restaurant is notified only after the link is clicked, and the link expires in 24 hours. It also warns that the confirmation link is deliberately not returned to the caller.

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, containing only four sentences. It front-loads the purpose and then provides essential instructions and warnings. Every sentence contributes necessary information without redundancy.

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

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

The tool has 7 parameters and no output schema. The description thoroughly explains the workflow and behavioral expectations, which is good. However, it does not mention what the tool returns (e.g., success indication or error), which is needed for an agent to use the tool effectively. Given the complexity, a brief note on return value 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?

The input schema has 100% description coverage, so the baseline is 3. The description adds value by emphasizing that the email parameter must be a real address belonging to the person being acted for and that the confirmation link is not returned. This provides behavioral context 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 'Request a table at a restaurant' and distinguishes it from a confirmed booking. It uses a specific verb and resource, and the context notes it's a request, not a confirmed booking, which differentiates it from sibling tools like create_booking.

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

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

The description explains when to use the tool and provides critical guidance: the restaurant is not notified yet, the confirmation email must be sent to a real address, and the user must check their inbox. However, it does not explicitly mention alternative tools or when not to use it, only implicitly through the request vs. booking distinction.

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

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

Fully discloses temporary nature, no payment taken, expiration of hold, and that tickets are not confirmed until checkout completed. No annotations exist, so description carries full burden and succeeds.

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 main purpose, followed by critical caveats and constraints. 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?

With no output schema, description explains return of checkout URL. Given sibling tools for events/tickets, this tool's role is well-defined. All constraints and behavior are covered.

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 3. Description adds value by specifying max limits (10 tickets, 10 ticket types) beyond schema definitions. Provides context that ticket IDs come from get_event_tickets and slugs from list_events.

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 it holds tickets and returns a checkout URL, with clear verb 'Hold' and resource 'tickets for an event'. Distinguishes from siblings by specifying it's only for Wix Events direct sales and directs to use ticketUrl elsewhere.

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?

Clearly describes when to use (Wix Events direct sales) and when not (external sites, use ticketUrl). Mentions constraints like max 10 tickets/ticket types. Could be improved by noting relation to create_checkout or create_booking, but 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?

Given no annotations, the description fully discloses the async behavior: confirmation email, link-based confirmation, expiry, and that the RSVP is only submitted after click. Also clarifies it is only for free events, no guest list initially, and the link is deliberately not returned.

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

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

The description is concise and well-structured: it starts with the purpose, then details critical behavioral notes and instructions. Every sentence provides necessary information without redundancy, making it efficient for an AI agent to parse and act upon.

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, the description adequately covers the entire RSVP process (async email confirmation, prerequisites, expectations). It provides sufficient context for the agent to understand the flow and instruct the user correctly, leaving no critical gaps.

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

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

Schema description coverage is 100%, so each parameter is already described. The description adds emphasis that email must be the guest's own and that event_slug comes from list_events, but these are not new semantics beyond the schema. Baseline 3 is appropriate as the description does not significantly augment parameter meaning.

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 'RSVP to a free event on this site (Wix Events)', specifying the action and resource. It distinguishes from sibling tools like reserve_event_tickets (for paid tickets) by emphasizing 'free event', making differentiation explicit.

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 'NOBODY IS ON THE GUEST LIST YET' and describes the confirmation email flow, including the 24-hour expiry and that the link is not returned. Instructs the agent to tell the user to check their inbox and use a real address, providing clear when-to-use and behavioral expectations.

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 explains search scope (every menu item, all restaurants, grouped by dish), return fields (price, description, dietary labels, URL), and behavior with/without query. No destructive or rate-limit info, but acceptable for a read-only search.

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, each informative. Front-loaded with core action. No redundant or extraneous information.

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

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

Given no output schema, description covers return fields well. Mentions 'neighborhood' but no location parameter exists; mild inconsistency. Overall, adequate for understanding tool's behavior and output.

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

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

Schema already describes both parameters (query and limit). Description adds value by explaining that omitting query returns top dishes and confirms limit's purpose. No additional semantic depth needed beyond this usage hint.

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 finds restaurants serving a dish, with grouping by dish and example. The verb 'find' is acceptable, and the context differentiates from sibling tools like search_places and get_restaurant_menus.

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

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

The description says 'Use this for any "where can I eat X" question', which gives clear context. However, it does not explicitly mention when not to use or list alternatives, such as search_places for general place search.

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 bears the burden of behavioral disclosure. It explains the typo-tolerant matching behavior, optional filtering by category/neighborhood, and the return of structured opening hours in Google Maps format. This gives the agent a clear understanding of what to expect.

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 long, with the first sentence stating the core purpose immediately. Each sentence adds distinct value: purpose, matching capabilities, and output format. No redundant or vague language.

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 4 optional parameters, no output schema, and no annotations, the description provides sufficient context for the agent to understand the tool's purpose, behavior, and output. It covers search terms, filters, and the special return of opening hours.

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 100% parameter description coverage, so baseline is 3. The description adds some context for the 'q' parameter (matching behavior) and mentions opening hours in results, but does not significantly elaborate on other 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 identifies the tool as a place search ('Search for places (restaurants, cafes, shops, etc.)'), uses a specific verb ('Search'), and names the resource ('places'). It distinguishes itself from sibling tools like 'get_place' (single place lookup) and 'search_dishes' (dish-specific search) by its broad 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?

The description implies when to use: for free-text searching of places in a neighborhood. It provides context on matching behavior (accent-insensitive, typo-tolerant) and optional filters. However, it does not explicitly state when not to use this tool or compare it to alternatives like 'get_place' for known places.

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

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

Discloses key behavior: submitting on behalf of user and returning a 'submissionId' upon success. No annotations provided, so description carries the burden 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?

Two concise sentences with no redundancy, front-loading the core action and necessary preliminary step.

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?

Complete for the tool's complexity: two parameters fully described, return value stated, and prerequisite noted. No output schema 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?

Schema covers 100% of parameters with descriptions; the description adds context by referencing 'list_forms' and providing an example for the fields object.

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'), and distinguishes itself from siblings like 'list_forms' by indicating it is the submission step.

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

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

Explicitly instructs to call 'list_forms' first to obtain required inputs (formId and field keys), but does not specify when not to use this tool.

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