Moema

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

No annotations are provided, so the description fully carries the burden. It discloses that payment is required, slots are re-validated, return is a checkout URL, and email is not verified, covering all critical behavioral aspects.

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

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

Front-loaded with purpose, then critical warnings. Efficient single paragraph without wasted words, though structure could be slightly clearer.

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 complexity (6 parameters, nested objects, no output schema), the description explains key behavior and required preconditions. Missing return value structure, but adequately complete for an agent.

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

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

Schema coverage is 100% with detailed parameter descriptions. The description adds workflow context but does not enhance parameter semantics beyond the schema. Baseline of 3 is appropriate.

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

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

The description clearly states 'Book an appointment slot at a venue (Wix Bookings)' and clarifies that nothing is booked until payment, distinguishing it from related tools like create_checkout and get_availability.

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

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

Provides explicit workflow guidance: call get_availability immediately before, the email is not verified, and the user must open the checkout link. Does not state when not to use, but the context is clear.

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

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

With no annotations, the description discloses that the tool creates a URL for payment completion by the user, and that no AI-side login is needed. It accurately implies a safe, non-destructive operation. Could be improved by explicitly stating the output format.

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

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

Two sentences with no wasted words, front-loaded with the core action and resource.

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

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

Given no output schema, the description should specify the return value (the URL). It implies the output but does not state it explicitly. It also implicitly requires prior listing of products, which is fine.

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 no additional semantics beyond what the schema already provides (e.g., 'Product ID from list_products' is already in the schema description).

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

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

The description clearly states the verb 'Create' and the resource 'direct checkout URL for one or more store products' with context 'Wix Stores'. It is unique among siblings as the only checkout creation tool.

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 generating a checkout URL and notes that no login is required on the AI side, providing clear context. However, it does not explicitly state when not to use or list alternatives.

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

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

No annotations are provided, so the description must cover behavioral traits. It discloses that returned times are in the venue's timezone (not necessarily the directory's), which is helpful. However, it does not mention other important behaviors like whether the operation is read-only, response format, or any limitations (rate limits, auth requirements). The description is minimally 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?

The description is two sentences long, front-loading the purpose and immediately proceeding to usage instructions and a key caveat. There is no redundant or extraneous information, making it efficient for an agent to parse.

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 no output schema, so the description should explain what the agent can expect in the response (e.g., structure of time slots, any limit). It does not mention return value format, pagination, or error handling. In the context of booking, the agent needs to know how to interpret the slots for downstream use (e.g., create_booking). This is a significant gap.

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

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

The input schema has 100% coverage with descriptions for all 3 parameters. The description adds value beyond the schema by clarifying the source of serviceId and place_slug (from list_booking_services) and the timezone nuance. It does not add technical details like parameter constraints beyond what 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 the tool retrieves available time slots for a bookable service on a given date, using Wix Bookings. It specifies the action (get available slots) and the resource (service), differentiating it from sibling tools like list_booking_services or create_booking.

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

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

The description instructs to pass serviceId from list_booking_services and a date in YYYY-MM-DD format, and to reuse the same place_slug. It includes a critical caveat about timezone being venue-specific. However, it does not explicitly state when not to use the tool (e.g., if service is not bookable) or mention alternatives.

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

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

No annotations provided; the description carries the burden. It discloses the return fields (ticket names, prices, sale status, how many left) and implies a read-only nature by not mentioning side effects. It does not cover authentication or rate limits, but for a simple query tool, it 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 main action, no filler. Every sentence adds value: first gives purpose and context, second gives usage guidance and expected 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 one parameter, no output schema, and no annotations, the description covers the essential: input (event slug from list_events), output fields, and context (Wix Events). Missing error handling or edge cases, but adequate for a simple retrieval tool.

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

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

Schema description coverage is 100% (one parameter with description). The description repeats the schema's parameter description ('Event slug from list_events') but adds context by explaining the tool's purpose. Baseline is 3 as coverage is high; the description adds marginal value over the schema.

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

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

The description clearly states the verb 'Get' and the resource 'ticket types and prices for a specific event (Wix Events)'. It distinguishes from siblings by referencing 'event slug from list_events', implying a prerequisite tool.

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 'Pass the event slug from list_events', providing a clear usage context. It does not explicitly state when not to use it, but the prerequisite makes it sufficiently clear for selection among siblings.

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

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

No annotations provided, so description carries full burden. It accurately describes a read operation with no side effects. Could mention that it requires no authentication hints or that it is safe, but the behavior is straightforward.

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, efficient sentence front-loading the purpose and then listing specifics. No wasted words.

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

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

Given no output schema, the description covers return values well. Might benefit from specifying the site scope (e.g., 'for the current site'), but overall adequate for a simple getter.

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; schema coverage is 100% trivially. Description adds no param info (unnecessary), but the baseline for zero-param tools is 4.

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

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

The description clearly states the tool retrieves loyalty/rewards program details for a site, specifying the resource (Wix Loyalty) and the exact data returned (program name, points currency name, tier structure). 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?

No explicit guidance on when to use this tool versus alternatives. However, sibling tools are largely unrelated (bookings, events, etc.), making the use case implicit. Lacks explicit when-not or alternative mentions.

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 mentions included fields (hours, ratings, etc.) but does not disclose authentication requirements, error handling, or absence of 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 a single sentence that front-loads the purpose and lists key output fields 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?

Despite lacking an output schema, the description covers the main output fields. However, it does not fully differentiate from 27 sibling tools, some of which also return details.

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 context about returned content but does not elaborate on the slug parameter 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 the tool gets full details for a specific place using a URL slug, distinguishing it from search tools like search_places.

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

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

The description implies use when you have a specific slug, but does not explicitly state when to use this tool over siblings like get_reviews or get_site_info.

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 details the return content (menus, sections, dishes, prices, dietary labels). While it doesn't cover error handling or rate limits, it is sufficient for a basic 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?

Two sentences with no wasted words. Front-loaded purpose and immediate usage guidance. Every sentence 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?

For a simple one-parameter tool with no output schema, the description fully covers functionality, return values, and prerequisite steps. It is complete given the 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?

Schema coverage is 100%, baseline 3. The description adds a concrete example (e.g., 'bar-do-ze') and clarifies the source of the slug (search_places or URL), enhancing understanding beyond the schema.

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

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

The description clearly states the tool retrieves a food menu for a specific restaurant, listing what it returns (sections, dishes, prices, dietary labels). This distinguishes it from sibling tools like search_dishes or get_place.

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

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

Explicitly instructs to use search_places or list_categories first to obtain the place_slug, providing clear prerequisite and pointing to relevant 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?

With no annotations, the description must stand alone. It correctly indicates a read operation but does not explicitly state 'read-only' or 'no side effects'. It lacks details on pagination, authentication, or rate limits, though the simplicity of the tool mitigates the gap.

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. Purpose and return fields are front-loaded. 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 read tool with one optional parameter, the description covers the essential: what it does and what it returns. Lacks mention of pagination or default limit, but the schema implies defaults. Slightly incomplete for advanced use, but adequate.

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

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

Schema coverage is 100% with the 'limit' parameter well-described. The description adds no extra 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 clearly states the action 'Get', the resource 'published reviews', and the context 'Wix Reviews'. It specifies the returned fields (reviewer name, rating, title, content), 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?

No explicit guidance on when to use this tool vs alternatives like list_offers or get_site_info. No prerequisites or exclusions are mentioned, leaving the agent to infer usage solely from the purpose.

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 burden. It transparently describes the return structure (cinema, session times, format, language) and the prerequisite. While it does not explicitly state read-only, the operation is intuitively retrieval-focused and no contradictory signals 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?

The description is two sentences: first states purpose and key details, second elaborates on output and a prerequisite. It is front-loaded, every sentence adds value, and there is no redundant or 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?

Given the simple tool with two parameters (fully described in schema), no output schema needed, and no annotations, the description covers all essential aspects: what it does, inputs, output structure, and a prerequisite. 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 description coverage is 100%, so baseline is 3. The description repeats the schema's parameter descriptions (date format, movie_slug example) without adding new semantic meaning beyond what the schema already provides. One extra prerequisite is noted but is not parameter-specific.

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

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

The description clearly specifies the action 'Get showtimes' for a specific movie, at cinemas in the neighborhood, for a given date. It distinguishes from sibling tools like list_movies and get_event_tickets by focusing on showtimes for a specific movie and providing details on returned fields (cinema, session times, format, language).

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 states a prerequisite ('Requires movies_enabled on this site') and implies that the movie_slug should come from list_movies via the parameter description. It does not explicitly mention when not to use the tool or compare to other siblings, but the context is clear enough for 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?

As no annotations are provided, the description carries the full burden of behavioral disclosure. It accurately describes the return contents (dynamic local time and weather) and implies a read operation. However, it does not explicitly state that the tool is read-only or has no side effects, though that is strongly implied.

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 lists outputs, second provides usage context. No redundant information. 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 no parameters and no output schema, the description fully covers what the agent needs to know: what the tool returns and when to use it. No gaps.

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

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

With zero parameters and 100% schema coverage, the description adds value by explaining what the tool returns without needing to elaborate on parameters. The baseline of 4 is appropriate as the description compensates adequately.

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

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

The description clearly specifies the tool returns basic directory info plus local time and weather, using specific elements like 'name, locale, domain, description, canonical URLs'. It distinguishes itself from sibling tools that focus on specific resources like bookings or events.

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

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

The description explicitly states 'Use this for any "what time is it there" or "what's the weather like" context', providing clear guidance on when to invoke this tool. No conflicting 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?

With no annotations provided, the description carries full weight for behavioral disclosure. It reveals that only published posts are returned (via 'published'), and lists return fields, but omits details like sorting order (likely descending by date), read-only nature, or pagination behavior beyond the limit parameter. The description is adequate but not exhaustive for a read-only tool.

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

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

The description is a single sentence that efficiently conveys the tool's purpose and output. It is front-loaded and contains no filler. While it could be structured with bullet points for readability, the current form is concise and direct, earning a 4 for its economy of 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 compensates by listing the specific fields returned (title, excerpt, author, etc.), which provides adequate contextual completeness for a simple list tool. Minor omissions like default sort order do not significantly detract, as the parameters are well-documented in the 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% as both parameters (limit, category) have descriptions. The tool description adds no new parameter information; it merely restates the tool's purpose. A baseline score of 3 is appropriate since the schema already documents parameters, and the description does not degrade but also does not enhance understanding.

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

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

The description clearly states the tool lists recent published blog posts for the Wix Blog site and enumerates the specific fields returned (title, excerpt, author, etc.). This directly specifies the verb (list), resource (blog posts), and scope, making it distinct from sibling tools that handle other content types like events or products.

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

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

The description implies usage for retrieving blog posts but does not explicitly state when to use this tool versus alternatives or when not to use it (e.g., for drafts or unpaged lists). No exclusions or alternative tool names are provided, leaving the agent to infer context from the tool name alone.

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 details return fields (name, description, price, duration, bookableViaMcp), explains behavior without place_slug, and warns that non-bookable services have null id, advising alternative 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?

Description is somewhat long but every sentence adds value. It is front-loaded with purpose. Minor redundancy (e.g., listing venue types) but overall efficient for the complexity.

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

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

With no output schema, description thoroughly explains output fields and edge cases. Covers both venue and directory services, booking status, and next steps for non-bookable entries. Fully complete for the tool's expected use.

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

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

Schema coverage is 100%, but description adds significant context: 'Strongly recommended — without it you get the directory's own services, not a venue's.' This clarifies the parameter's critical role 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's purpose: 'List a venue's services — what it offers, with price and duration.' It specifies the resource (venue's services) and action (list), and distinguishes from siblings like search_places 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 place_slug (for venue services) and when to omit (for directory's own services). States 'that is what you want in almost every case' and warns about bookableViaMcp=false, guiding the agent toward correct usage.

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

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

No annotations provided; the description discloses the output content (top-level groups, subcategories, labels, types, place counts) but does not mention potential limitations, prerequisites, 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 a single, well-structured sentence that front-loads the action and includes all necessary details without redundancy.

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

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

Given no parameters, no annotations, and no output schema, the description adequately explains the tool's purpose and output. It could benefit from mentioning pagination or structure but is still reasonably 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?

No parameters exist in the input schema, so baseline is 4. The description adds value by explaining what the output contains, which is 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 specifies that the tool returns the full category taxonomy with specific elements (top-level groups, subcategories, localized labels, schema.org types, live place counts). It distinguishes from sibling list tools by explicitly mentioning the category taxonomy.

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 the category taxonomy is needed, but does not explicitly state when to use vs alternatives or provide 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 the full burden. It reveals the behavioral detail that filter 'agora' is resolved live on every call, which adds transparency. However, it does not disclose whether the tool is read-only, potential rate limits, or required authentication, leaving some gaps for a listing tool.

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

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

The description is composed of three concise sentences, each adding distinct information: purpose and output, weather detail, and filter usage with an example. It is front-loaded and contains no filler, making it efficient for an agent to parse.

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 (3 optional params, no output schema) and the richness of sibling tools, the description is mostly complete. It covers what events are returned and how to filter. However, it lacks details on pagination, default behavior (e.g., upcoming_only default true is documented in schema but not reinforced), and error handling.

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 all three parameters. The description adds value beyond the schema by explaining the weather inclusion context, giving an example of filter usage, and elaborating on the 'agora' filter's live resolution. This enriches the agent's understanding of how parameters affect output.

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

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

The description clearly states the tool lists upcoming events with specific output fields (date, venue, price, URL) and mentions weather forecasting for near-term events. It distinguishes itself from sibling list tools (e.g., list_blog_posts, list_products) and event-related tools (e.g., get_event_tickets, rsvp_event) by focusing on event discovery and context.

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

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

The description provides usage context by explaining how to use the `filter` parameter to narrow results (e.g., 'agora' for current events) and mentions it is resolved live. However, it does not explicitly state when NOT to use this tool or compare it with alternatives like list_offers or list_blog_posts, lacking explicit exclusions.

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

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

No annotations are provided, so the description must disclose behavioral traits. It states the output is grouped by category, which is useful, but does not explicitly label the tool as read-only or mention any side effects, rate limits, or pagination. The behavioral transparency is adequate but not enhanced.

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 only two sentences, front-loading the core action and purpose. Every sentence adds value with no redundancy or unnecessary detail.

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

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

Given the tool's simplicity (no parameters, no output schema), the description fully covers what the tool does and when to use it. It is complete for an agent to select and invoke the tool correctly.

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

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

The tool has no parameters (schema coverage 100% with empty properties). The description adds context about the returned data (grouped by category) but does not need to explain parameters. Baseline for zero-parameter tools is 4.

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

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

The description explicitly states 'Get all FAQ questions and answers for this site' and 'Grouped by category,' providing a clear verb and resource. It distinguishes from sibling tools by specifying FAQ content and gives concrete examples of use (opening hours, parking, policies).

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

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

The description advises 'Use this to answer common questions about the site,' giving clear usage context. It does not explicitly mention when to avoid the tool or provide alternatives, but the examples and tool name imply a straightforward use case.

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?

While no annotations exist, the description adequately explains behavior: returns form details. Lacks details on empty results or error conditions, but acceptable for a straightforward 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?

Two concise sentences with no redundancy, front-loading purpose and return details, then usage guidance.

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

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

Given the tool's simplicity (0 params, no output schema), the description fully covers its purpose and integration point with submit_form.

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

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

No parameters in input schema (100% coverage by empty schema). Description does not need to add parameter info; baseline for zero-parameter tools is 4.

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

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

The description clearly states the tool lists available contact/signup forms on Wix Forms, specifies return values (name, ID, field definitions), and distinguishes it from submit_form by indicating its role as a precursor.

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 use 'before submit_form to discover which fields to fill', providing clear workflow guidance. No additional exclusions needed for a simple list 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. States it lists ranked places with editorial notes, but does not disclose pagination behavior (only implied by limit parameter) or whether results are ordered. Basic transparency but missing details.

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 sentence defines the tool's function, second sentence provides usage context. 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 one parameter with full schema coverage, no output schema, and no annotations, the description appropriately explains what the tool returns and when to use it. Could mention ordering or filtering, but adequate for a simple list tool.

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

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

Schema coverage is 100% with a single parameter that has a description. The tool description does not add additional meaning beyond what the schema already provides. Baseline 3 is appropriate.

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

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

Description clearly states it lists curated editorial guides ('best of' lists) with editorial notes, and specifies they are ranked places. The verb 'list' matches the tool name. It distinguishes from sibling tools like list_blog_posts by focusing on editorial guides.

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

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

Explicitly states 'The best source for 'best X in this neighborhood' questions,' providing clear context for when to use. No explicit when-not-to-use or alternatives, but the usage context is clear enough.

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 bears full responsibility for behavioral transparency. It clearly describes the tool's read nature and the data it returns (now-showing, coming-soon, streaming). It does not mention authentication or rate limits, but for a list tool this is acceptable.

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

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

The description is two sentences long, front-loads the main purpose, and includes all key details without any wasted words. Every sentence adds value.

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

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

Given no output schema, the description adequately informs the agent about returned fields and input parameters. It could mention pagination details or default limits, but overall it is complete enough for a list tool.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context by explaining the enum values in more detail (e.g., exactly what each status means for local cinemas and streaming services), going beyond the schema descriptions.

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

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

The description specifies the exact action: listing movies available in a neighborhood, with conditions ('only on sites with movies_enabled') and includes the types of movies (now-showing, coming-soon, streaming) and returned fields (title, genres, rating, etc.), clearly distinguishing from sibling list tools.

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

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

The description states the condition 'only on sites with movies_enabled', giving clear context for use. However, it does not explicitly state when not to use this tool or directly compare to alternatives like list_events. The guideline is strong but could be more explicit about 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 burden. It describes return fields and notes FLASH offers have countdown deadlines, but doesn't disclose any side effects, authentication requirements, rate limits, or idempotency. For a read-only list tool, this is adequate but minimal.

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

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

Three concise sentences with no redundancy. The first sentence states purpose, the second details return fields, the third highlights FLASH offers. 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?

Given no output schema, the description covers return fields adequately. It could mention pagination beyond limit, but 0 required parameters and simple filter make it mostly self-contained.

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 (kind and limit). The description adds value by explaining FLASH kind as 'time-limited flash sale with countdown', but this is a minor addition. 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 active promotions and deals, specifies return fields (discount, promo code, CTA link, validity, business), and distinguishes FLASH offers with countdown deadlines. This is specific and distinct from sibling 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?

The description implies usage for browsing available offers in the neighborhood directory. The mention of 'active promotions and deals' and 'FLASH offers' provides context but doesn't explicitly state when to use this tool versus alternatives like get_loyalty_info or list_pricing_plans.

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 explicitly lists return fields (name, price, billing cycle, perks, checkout URL), which is transparent. No side effects or destructive actions are suggested.

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

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

Single sentence that front-loads action and resource, immediately followed by return details. Every word adds value—no redundancy or irrelevant information.

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

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

With no output schema, description compensates by listing returned fields. No mention of pagination or ordering, but for a simple list of all plans, it is adequate. Sibling tools indicate many listing tools, but this one stands alone.

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

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

No parameters in schema (0 required). Schema coverage is 100% (empty). Baseline for 0 parameters is 4; description adds no param info but none needed. Handled well.

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 specifies verb 'list', resource 'pricing plans', and includes context '(Wix Pricing Plans)'. It clearly distinguishes from sibling tools like 'list_products' or 'list_blog_posts' by focusing on membership/subscription plans.

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 for retrieving plan details but does not explicitly state when to use it over alternatives or provide exclusions. Context signals show no parameters, making usage straightforward.

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

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

No annotations provided. Description does not explicitly state that the operation is read-only or idempotent, but listing is inherently non-destructive. Basic disclosure of return fields, but lacks depth on behavior like pagination or rate limits.

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

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

Single sentence, efficient, front-loaded with key information. No wasted words.

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

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

Despite no output schema, description lists return fields. With low complexity (2 optional params) and clear sibling context, it provides enough information for basic usage.

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

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

Schema coverage is 100%, so description adds no additional meaning beyond schema descriptions. Parameters 'q' and 'limit' are adequately 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?

Clearly states verb 'List', resource 'products', specifies store type (Wix Stores) and return fields (name, price, stock status, product type). Distinguishes from siblings like list_blog_posts and list_events.

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

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

Description is clear about what it does but offers no guidance on when to use it vs. alternatives, no context on 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 must carry the burden of behavioral disclosure. It describes what is returned (name, URL, category, metadata) but omits details like pagination limits (beyond the limit parameter), ordering, or side effects. The read-only nature is implied but not explicit.

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

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

The description is two sentences with no unnecessary words. It front-loads the core action and then adds clarifying details and examples efficiently.

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

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

For a simple list tool with no output schema, the description sufficiently explains the return fields and the type of profiles. It could mention whether pagination is supported beyond the limit parameter, but it is largely complete for the tool's purpose.

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 purpose of the returned fields (e.g., 'any available metadata (age, height, etc.)'), which enhances understanding beyond the schema's parameter definition.

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

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

The description specifies a clear verb ('List') and resource ('solo service-provider profiles'), defines the type of businesses (no fixed physical location), and provides concrete examples (dog walkers, tutors). This distinguishes it from sibling tools like list_categories 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?

The description clearly indicates when to use the tool—to list solo service-provider profiles. It does not explicitly state when not to use it or mention alternatives, but the context of sibling tools makes the usage context clear.

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

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

Discloses that the request is held, confirmation email is sent, link expires in 24 hours, and the link is not returned to the agent. No annotations provided, but description covers all behavioral aspects.

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?

Four sentences, each essential. Front-loaded with main purpose, 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?

Covers all behavioral details: the flow, expiration, and role of email. No output schema needed for this tool's 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?

Schema description coverage is 100%, so baseline is 3. Description adds value by stating that email must be the guest's own and that place_slug comes from search_places.

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.

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?

Explains that the restaurant is not notified yet, the user must check email, and that the restaurant confirms out of band. Implicitly distinguishes from create_booking, but does not explicitly list when not to use.

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

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

No annotations provided, so the description carries full burden. It discloses that the hold is temporary, not paid, expires automatically, and only works for certain events. Also states limits. This is comprehensive behavioral context.

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 main action, then caveats and exceptions. Every sentence carries essential information. 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?

No output schema, but description states the return value (checkout URL). Covers behavior, limits, exceptions, and usage context. Complete for a tool with 2 simple 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?

Schema description coverage is 100%, so parameters are already well-documented. The description adds context by explaining the workflow (hold then checkout URL) and reinforcing the source of event_slug and tickets. It adds value beyond the schema, but not significantly new semantics.

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

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

The description clearly states the tool holds tickets for an event and returns a checkout URL. It specifies the verb (hold) and resource (event tickets), and distinguishes from siblings like create_booking or rsvp_event by mentioning it's for Wix Events and returns a checkout URL.

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 (for events sold through this site) and when not to (for events sold elsewhere, use the event's own ticketUrl). Also explains the temporary nature, that the hold expires, and the need for human checkout. Mentions limits (max 10 tickets, 10 ticket types).

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

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

With no annotations, the description fully discloses the tool's asynchronous nature: no immediate RSVP, a confirmation email must be clicked, link expires in 24 hours. It also states the link is deliberately not returned to the agent, setting expectations clearly.

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 four sentences, each essential. It front-loads the core purpose, then immediately delivers critical behavioral and usage instructions without redundancy or fluff. 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 4 required params, no output schema, and no annotations, the description covers purpose, behavior, and usage guidance thoroughly. It does not mention the return value (likely a confirmation message), but for an initiation tool this is a minor gap. Overall, it provides sufficient context for correct invocation.

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

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

Schema coverage is 100% with adequate descriptions for all 4 parameters. The tool description adds value beyond the schema by emphasizing that the email must be a real address belonging to the person being acted for, reinforcing ownership. This extra context elevates it above baseline 3.

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

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

The description clearly states 'RSVP to a free event on this site (Wix Events)', specifying the action, resource, and constraint (free events). It distinguishes from sibling tools like 'reserve_event_tickets' which likely handles paid events, and provides unique caveats about the confirmation process.

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 the agent when to use this tool (for free events requiring email confirmation), instructs to tell the user to check their inbox, warns that the confirmation link is not returned, and advises using a real address. It effectively guides correct invocation without confusing with 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?

With no annotations, the description fully discloses that it searches all menus, groups results by dish, and returns price, description, dietary labels, and place URL. It also covers the special case of omitting query. No mention of auth or rate limits, but for a search tool 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: first states the core purpose, second provides a detailed example and behavior for omitted query. No fluff, front-loaded with essential info.

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

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

Without an output schema, the description lists return fields and covers both query and no-query cases. Lacks details on sorting or pagination beyond limit, but is sufficient for a simple search tool.

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

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

Schema coverage is 100% with clear descriptions for both parameters. The tool description adds value by explaining how results are grouped and what fields are returned, going beyond the schema's basic type and default info.

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

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

The description clearly states the verb 'Find', the resource (dishes), and the scope (neighborhood, all restaurants). It distinguishes from siblings like 'get_restaurant_menus' by focusing on dish-level search across venues, and provides a concrete example.

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 use for 'where can I eat X' questions and describes behavior when query is omitted. While sibling differentiation is implicit, the context is clear and actionable.

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

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

No annotations provided, so description carries full burden. Explains accent-insensitive and typo-tolerant matching, relevance ranking, and structured opening hours format. Lacks mention of pagination or error cases, but adequate for a search tool.

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

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

Two sentences, front-loaded with purpose, each sentence adds value. No redundancy or waste.

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

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

No output schema, so description must cover return values. Explains structured opening hours but omits other common fields (name, address, rating). Still sufficient for search tool usage.

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

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

Schema coverage is 100% (baseline 3). Description adds meaning beyond schema for 'q' (explains accent-insensitive, typo-tolerant) and return value format for opening hours.

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?

Specifies a clear verb ('Search') and resource ('places'), listing examples (restaurants, cafes) and distinguishing from siblings like get_place (single place) and search_dishes (specific dish).

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?

Describes optional filters and contextual scope ('in this neighborhood'), but does not explicitly state when to use alternatives like get_place for exact queries.

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

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

No annotations are provided, so the description carries full burden. It discloses that a 'submissionId' is returned on success, indicating a write operation. However, it does not detail side effects, authorization requirements, or potential failure modes, leaving some ambiguity for an agent.

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 serving a distinct purpose: first states the action, second provides prerequisite and return info. No wasted words, front-loaded with 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?

Given the tool's simplicity (2 parameters, no output schema), the description covers the essential flow: prerequisite (list_forms), input (formId, fields), and output (submissionId). No gaps for an agent to successfully use this tool.

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

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

Schema description coverage is 100%, but the description adds value by providing a concrete example ('{ "field_1": "João", "field_2": "joao@email.com" }') and clarifying that fields are key-value pairs matching 'list_forms' field keys. This goes beyond the schema's generic descriptions.

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

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

The description clearly states the action ('Submit a form'), the resource ('form on behalf of the user'), and the platform ('Wix Forms'). It distinguishes from the sibling tool 'list_forms' by mentioning calling it first, implying this is the write counterpart.

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 the agent to call 'list_forms' first to obtain formId and field keys. This provides clear prerequisite context. However, it does not mention when not to use this tool or any alternatives, though for this simple submission tool it is sufficient.

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