Paraíso

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

Without annotations, the description fully discloses behavioral traits: returns checkout URL, booking stays off calendar, contact email not verified, slot re-validated. No hidden 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?

Single paragraph with key warnings front-loaded in capitals. Every sentence adds unique value, 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?

Complete for a complex tool: covers pre-requisites, return behavior, user guidance, and error cases. No missing information despite lacking output 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%, and description adds value by linking parameters to other tool outputs (e.g., startDate/endDate from get_availability, serviceId from list_booking_services) and providing validation hints (phone 10+ digits).

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

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

Clearly states it books an appointment slot, with crucial caveat that nothing is booked until payment. Distinguishes itself from a naive 'create' by emphasizing the non-final nature.

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 specifies pre-condition (call get_availability immediately before), mentions server-side re-validation, and instructs the agent to tell the user to open the checkout URL. Provides when-to-use and failure handling.

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

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

The description discloses that the tool initiates checkout and the user clicks the URL to pay, which is key behavior. However, it does not mention side effects (e.g., order creation), URL expiry, or failure handling. With no annotations, the description carries the full burden, but the missing details lower the score to minimal viable.

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. It front-loads the purpose and adds a key behavioral note. 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 output schema, the description should explain what the tool returns (a URL) and its format. It mentions the user clicks the URL, but does not describe the return value or error handling. The description is adequate for simple use but incomplete for a fully self-contained tool definition.

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 each property. The description adds context by stating 'one or more store products' and 'no login required', but these align with the schema rather than adding significant new meaning. 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 tool creates a direct checkout URL for one or more Wix Stores products. It uses specific verb 'create' and resource 'checkout URL', and distinguishes itself from siblings as the only checkout-related 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 mentions that no login is required on the AI agent side, providing a clear usage context. It implies the user completes payment, but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives, such as for complex checkout scenarios or when login is required.

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

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

The description discloses a behavioral trait: slot times are in the venue's timezone, not the directory's. With no annotations provided, the description carries full burden. It lacks details on side effects (likely read-only), handling of unavailable slots, or response structure, but the timezone note is valuable.

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, front-loaded with the main action, and efficient. It avoids redundancy but could be slightly more structured (e.g., listing parameters). Still, every sentence adds value.

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

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

No output schema exists, so the description should clarify return format. It mentions 'available time slots' but not structure, pagination, or error cases. Given the tool's simplicity (3 params, no nested objects), the description is adequate but not fully complete.

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

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

Input schema coverage is 100%, so each parameter already has a description. The tool description adds little new: it reinforces the relationship to list_booking_services and place_slug, but doesn't add semantics beyond what the schema provides. Baseline is 3.

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

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

The description clearly states the tool's purpose: 'Get available time slots for a bookable service on a given date'. It specifies the domain (Wix Bookings) and distinguishes from siblings like list_booking_services by referencing it as a prerequisite. However, it does not explicitly differentiate from other time-related tools like get_showtimes or get_event_tickets, which are also siblings.

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

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

The description provides usage instructions: pass serviceId from list_booking_services, a date in YYYY-MM-DD, and the same place_slug. It also warns about timezone behavior. However, it does not state when NOT to use this tool (e.g., if the service is not bookable) or suggest alternatives among siblings, leaving some ambiguity.

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 the full burden. It discloses that the tool is a read operation ('Get') and explicitly lists return values. Lacks details on authentication or rate limits, but for a simple query 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 concise sentences with no superfluous information. Every word serves a purpose: stating the action, source, and return data.

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 fully covers what it does, how to use it, and what it returns. 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?

The only parameter 'event_slug' has 100% schema coverage with a description matching the tool's description. The description reiterates the schema, adding no new semantic value 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 retrieves ticket types and prices for a specific event, explicitly listing returned fields (names, prices, sale status, quantity left). It distinguishes from sibling tools like 'reserve_event_tickets' and 'rsvp_event' by focusing on data retrieval.

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 a clear prerequisite: pass the event slug from 'list_events'. This guides the user on required preparation. However, it does not explicitly state when not to use this tool (e.g., for purchasing tickets), but the context is clear given siblings.

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

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

No annotations are provided, so the description carries the full burden. It states the tool returns certain fields, but it does not disclose whether authentication is required, if the operation is read-only, or any potential side effects. It also does not explain the scope ('for this site').

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 communicates the purpose and return information without redundant words. It is appropriately sized.

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

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

The description covers the key return fields (program name, points currency, tier structure). However, it lacks details about potential additional data or limitations, which could be useful given the absence of an output 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?

There are no parameters, so schema coverage is 100%. The description adds value by explaining what the tool returns, which is sufficient given the zero-parameter input 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', the resource 'loyalty/rewards program details for this site', and specifies the return values (program name, points currency name, tier structure). It implicitly distinguishes from sibling tools that retrieve other types of 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 usage when loyalty program details are needed, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or 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 details the returned data (opening hours, open_now, attributes, delivery array, ratings, address, neighborhood) and the input parameter, providing good transparency for a read-only operation. No side effects or permissions mentioned, but acceptable for a simple retrieval.

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

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

The description is a single, information-dense sentence that efficiently lists all returned fields. It is well-structured with commas and examples for clarity, though it could be slightly front-loaded differently.

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

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

Given no output schema and a single parameter, the description adequately covers the return structure, including nested elements like the delivery array with platform and url. It fully addresses what the agent needs to know for 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 coverage is 100%, so baseline is 3. The description reinforces the slug parameter as a URL slug, matching the schema's description. It adds no new semantic information but remains consistent.

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 full details for a specific place by its URL slug, listing specific fields like opening hours, open_now, attributes, and delivery links. This distinguishes it from siblings like search_places that likely list multiple 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 usage when a place's URL slug is already known, contrasting with search_places for discovery. It provides clear context but lacks explicit when-to-use or alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the output content (sections, dishes, prices, dietary labels) but does not explicitly state that the tool is read-only, nor does it mention any side effects, rate limits, or authorization requirements. The description is adequate but lacks explicit non-destructive declaration.

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 comprises two concise sentences with no extraneous information. The first sentence fronts the core purpose, and the second provides essential usage guidance, making it efficient and easy to scan.

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 one well-documented parameter and no output schema, the description sufficiently explains both the input (how to get place_slug) and the output (menu contents). It covers all necessary aspects for a simple data 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 coverage is 100% for the single parameter place_slug, and the description enriches it by explaining the source (from search_places or a URL) and providing a concrete example ('bar-do-ze'). This adds meaningful context beyond the schema 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 clearly states that the tool retrieves the food menu for a specific restaurant, listing detailed contents such as sections, dishes, prices, and dietary labels. This distinguishes it from siblings like search_dishes (searching across restaurants) and search_places (finding restaurants).

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

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

The description explicitly tells users to use search_places or list_categories first to obtain the required place_slug, providing clear sequential guidance. It does not mention when not to use the tool, but the prerequisite instruction is valuable.

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 bears full burden. It discloses the return format but omits important behavioral traits such as read-only nature, required permissions, or any rate limits. For a tool that presumably reads data, this is a notable 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?

The description is two sentences, direct and void of unnecessary information. Every word adds value, making it easy to parse quickly.

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 structure (one parameter, no output schema), the description sufficiently covers what the tool returns. However, the lack of output schema means the description must compensate, and it does by listing return fields. Minor gap: no mention of ordering or default behavior beyond the schema's 'default 10'.

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 100% schema description coverage and a single parameter ('limit'), the description adds no extra meaning beyond the schema. The baseline score of 3 is appropriate as the schema already documents the parameter's purpose and constraints.

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') and the resource ('published reviews') and explicitly lists the returned fields (reviewer name, rating, title, content). This distinguishes it from sibling tools like list_products or get_site_info.

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 it returns reviews 'for this site' but does not provide guidance on when to use this tool versus alternatives (e.g., list_blog_posts for content not reviews). No exclusions or prerequisites 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 provided, the description carries the full burden. It discloses that the tool returns dynamic data (current local time and weather), which is a key behavioral trait. It does not mention any side effects or auth requirements, but for a read-only tool this is sufficient. A score of 4 is appropriate.

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 with no wasted words. It front-loads the main purpose and ends with concrete usage examples. Every part 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 zero parameters, no output schema, and the tool's simple nature, the description is fully complete. It covers what data is returned and when to use the tool. There are 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?

The input schema has zero parameters, so the description cannot add information about parameters. Baseline for 0 params is 4. The description explains the output fields, which adds meaning 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 'returns basic information about this neighborhood directory' including specific items like name, locale, domain, and canonical URLs, plus current local time and weather. This verb-resource pairing is specific and distinguishes it from sibling tools like get_place which focus on individual 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 explicitly says 'Use this for any 'what time is it there' or 'what's the weather like' context', providing clear usage scenarios. However, it does not explicitly state when not to use it or compare directly with siblings, so it loses a point for missing 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 exist, so the description bears full burden. It correctly implies a read-only operation but does not mention authentication requirements, rate limits, pagination, or any side effects. The behavior is adequately stated but lacks depth.

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

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

Two efficient sentences: first states the action and scope, second lists return values. Zero waste, front-loaded, and easy 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?

Without an output schema, the description compensates by listing return fields. It is sufficient for basic use but lacks details on ordering (e.g., most recent first), error behavior, or limits on page size beyond the 'limit' parameter. Good but not fully comprehensive.

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

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

Schema description coverage is 100% with both parameters (limit, category) described. The description adds no further parameter context beyond listing return fields. Baseline 3 is appropriate as the schema already does the heavy lifting.

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

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

The description clearly states the tool lists recent published blog posts for a Wix Blog and enumerates specific return fields (title, excerpt, etc.). It is distinct from sibling tools which cover different resources like bookings, products, 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?

No explicit guidance on when to use this tool versus alternatives or when not to use it. Usage is implied by the name and description, but no exclusions or context provided. Sibling tools are diverse so more differentiation would help.

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 bears full burden. It discloses that services are returned for all venues, including those without online booking, and explains the bookableViaMcp flag and null id behavior. Lacks explicit mention of read-only nature but covers key behavioral traits.

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

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

Well-structured with front-loaded purpose, followed by clarifications. Each sentence adds unique information without redundancy. Efficient use of 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?

For a simple listing tool with one optional parameter and no output schema, the description adequately mentions key output fields (name, description, price, duration, bookableViaMcp) and handles the edge case of non-bookable venues. Could mention pagination or list format, but overall complete.

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

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

Schema coverage is 100%, baseline 3. The description adds value by explaining the dual behavior of place_slug, emphasizing it is strongly recommended, and linking serviceId usability with create_booking. This goes beyond the schema's parameter 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 it lists a venue's services with price and duration, and distinguishes between two modes (with or without place_slug). It uses the verb 'list' matching the tool name and effectively differentiates from sibling tools like create_booking 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?

Explicitly tells when to use each mode: pass place_slug from search_places for venue services (usual case), omit for directory's own services (rare). Advises checking bookableViaMcp to handle non-bookable venues and mentions that only venue serviceId works with create_booking.

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

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

No annotations are provided, so the description must disclose behavior. It describes the returned data but does not explicitly state that the operation is read-only or mention any performance, authorization, or caching characteristics.

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 efficiently conveys the tool's purpose and detail. No unnecessary words, and key information is front-loaded.

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

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

The description explains the return value contents adequately for a taxonomy listing. However, it does not mention pagination, ordering, or whether the taxonomy is cached, which could be relevant for agents.

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

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

The tool has no parameters, and the description adds no parameter information, which is acceptable. The baseline score for zero parameters 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 uses the specific verb 'Returns' and clearly identifies the resource as 'full category taxonomy' with detailed inclusions. It effectively distinguishes from sibling list tools which target different domains.

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

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

While the description does not explicitly state when to use this tool over alternatives, its focus on category taxonomy and the context of sibling tools make the usage straightforward. A clear statement of when not to use it is absent.

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 events within 7 days include a weatherForecast and that the 'agora' filter is resolved live (uncached). This adds useful behavioral context beyond the schema. The description does not mention any side effects or destructive actions, which is fine as this is likely a read operation.

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

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

The description is two sentences, front-loaded with the core purpose, followed by concise details on weather forecast and filter usage. Every phrase 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, the description specifies returned fields (date, venue, price, URL, plus weatherForecast for 7-day events). Parameter usage is well explained. However, it does not mention sorting, pagination beyond limit, or error conditions, though these are not critical given the tool's simplicity.

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

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

Schema coverage is 100% with descriptions for all 3 parameters. The description adds significant value by explaining the filter values in detail, especially the live behavior of 'agora'. The limit and upcoming_only parameters are adequately covered by 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 'List upcoming events in this neighborhood with date, venue, price, and URL.' It specifies the verb (list), resource (upcoming events), and key fields. However, it does not explicitly differentiate from sibling tools like list_movies or list_offers, though the neighborhood context is implicit.

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

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

The description provides explicit guidance on using the `filter` parameter, including detailed explanations for each enum value, especially 'agora' which is noted as live-resolved. However, it does not directly compare with sibling tools or state when NOT to use this tool.

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

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

No annotations are provided, so the description carries the full burden. It states the tool returns FAQs grouped by category, but does not disclose any limitations, data freshness, or response structure. Basic transparency is present.

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

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

Two sentences, front-loaded with the action ('Get all FAQ questions and answers') and purpose. Every sentence is necessary and no wasted words.

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

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

Without an output schema, the description clearly indicates the structure (questions and answers, grouped by category). For a simple read tool, it is sufficiently complete.

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

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

There are no parameters (0 params, 100% schema coverage). The description adds value by explaining the type of data returned, which compensates for the lack of parameters. Baseline for 0 params is 4.

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

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

The description clearly states it retrieves FAQ questions and answers, grouped by category, with specific use cases (opening hours, parking, etc.). It effectively distinguishes from siblings by being the only FAQ-related 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 says 'Use this to answer common questions about the site', providing clear usage context. It does not specify when not to use it or alternatives, but given the distinct purpose, it is adequate.

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

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

No annotations are provided, so the description carries full burden. It describes the tool's behavior (listing forms, returning fields) and implies a read-only operation. No side effects mentioned, but none 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?

Two concise sentences, front-loaded with purpose, no extraneous text.

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

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

Given zero parameters and no output schema, the description fully covers what the tool does and when to use it. No gaps identified.

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

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

The input schema has no parameters (100% coverage), so baseline is 4. Description adds no parameter info, but none is needed.

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

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

The description clearly states it lists available contact/signup forms (specific resource) and specifies return fields (name, ID, field definitions). It distinguishes itself from sibling tool 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 context and naming an alternative.

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 burden but only mentions that guides are ranked places with editorial notes; lacks details on output format, ranking methodology, or pagination behavior.

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

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

Two sentences, each providing essential information without redundancy, achieving high density of useful 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 absence of output schema and moderate complexity, the description provides sufficient differentiation from siblings but lacks details on returned fields or default behavior beyond limit.

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

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

The only parameter 'limit' is fully described in the schema (coverage 100%), and the tool description adds no additional semantics beyond the schema.

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

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

The description clearly states the tool lists curated editorial guides ('best of' lists) with ranked places and editorial notes, which distinguishes it from sibling list tools for other entities.

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

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

Explicitly suggests use for 'best X in this neighborhood' questions, providing clear context for when to use, though no explicit exclusions or alternatives 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?

No annotations provided, so description must disclose behavior. It mentions return fields and FLASH countdown but lacks side-effect info, auth needs, or read-only guarantee. Adequate but not thorough.

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

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

Three concise sentences with front-loaded purpose. No wasted words, clear structure.

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?

Explains return fields and FLASH distinction. Lacks pagination details (e.g., offset, default ordering) and whether the list is exhaustive. Good but incomplete 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 covers both parameters 100%, baseline 3. Description adds context about FLASH offers relating to kind enum but does not enrich limit parameters beyond schema. Minimal added value.

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

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

Description clearly states the tool lists active promotions/deals in a neighborhood directory, specifies return fields (discount label, promo code, etc.), and distinguishes FLASH offers. Differentiates well from sibling list tools for other entities.

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

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

Description implies the tool is for promotions but does not provide explicit guidance on when to use it vs. siblings (e.g., list_events, list_products). No when-not-to-use or alternative cues.

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. Discloses that it's a list operation (read-only implied) and specifies return fields. Does not mention auth/rate limits but that's acceptable for a simple list tool. No contradictions.

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

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

Two sentences, front-loaded with purpose. No redundant information. 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?

Complete for a list tool with one optional parameter. Explains return fields (name, description, price, etc.). No missing information for expected 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?

Only parameter place_slug is described in schema (100% coverage). Description adds value by explaining its provenance ('from search_places') and the effect of omission ('without it you get the directory's own plans'). Adds context 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?

Specific verb 'List' and resource 'membership or subscription plans (Wix Pricing Plans)'. Distinguishes between listing venue plans (with place_slug) and directory's own plans (without). Clearly defines scope.

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

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

Explicitly states when to use place_slug ('that is what you want in almost every case') and when to omit it. Mentions source of slug from search_places, linking to sibling tool. Provides clear guidance on typical 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 are provided, so the description carries the burden. It discloses that the tool returns specific fields and is associated with Wix Stores, but it does not mention whether it is read-only, pagination behavior, authentication needs, or cost. Basic transparency is present but incomplete.

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 returned fields without any filler. It is front-loaded and 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 the tool's simplicity and the presence of a complete input schema, the description covers the returned fields adequately. However, it omits details like ordering or pagination behavior beyond the limit parameter. Still, it is largely complete for a listing tool.

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

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

Schema coverage is 100%, with both parameters already well-described in the schema. The description adds no new meaning beyond affirming the search term matches product name, so it meets the baseline but does not exceed it.

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

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

The description clearly states the action ('List products') and the resource ('in this site's store'), and it specifies what is returned (name, price, stock status, product type). It is distinct from sibling tools, all of which target different entities.

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

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

The description implies usage for listing store products but provides no explicit guidance on when to use this tool over siblings or when not to use it. No alternatives or exclusions 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 provided, the description must disclose behavioral traits. It mentions return fields (name, profile URL, category, metadata) but omits whether the tool is read-only, requires authentication, supports pagination beyond the limit parameter, or has any side effects. This is minimal transparency for a tool that is likely safe and read-only.

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

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

The description is a single sentence with a clarifying parenthetical, no redundant words. It is front-loaded with the key action and resource, earning every sentence's place. Excellent conciseness.

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

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

Given the simplicity (one optional parameter, no output schema) and no annotations, the description covers the essential what and output. However, it lacks details on default behavior (default limit 50 is in schema), ordering, pagination, or how this tool contrasts with other list tools. It is adequate but not thorough.

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 one parameter (limit) with 100% description coverage, so the baseline is 3. The tool description adds no extra context about the parameter beyond what the schema already provides. Thus, no improvement over 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 specifies the verb 'List' and the resource 'solo service-provider profiles'. It distinguishes this tool from sibling listing tools by describing the specific type of profiles (businesses without a fixed physical location) and provides concrete examples. This makes the purpose unambiguous and differentiated.

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 (when needing profiles of solo service-providers) but does not explicitly state when not to use or provide alternatives. Among many listing siblings, no exclusion or comparison is given, leaving the agent to infer the 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 fully describes the tool's behavior: the request is held, a confirmation email is sent, the restaurant is notified only after the user clicks, the link expires in 24 hours, and the confirmation link is not returned to the agent. This is comprehensive and honest.

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

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

The description is concise with about 4 sentences, each adding critical information. It front-loads the purpose and then delivers behavioral caveats efficiently. Could be slightly improved with clearer separation of points.

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 multi-step workflow (email confirmation, expiry, out-of-band restaurant confirmation) and no output schema, the description covers essential post-invocation actions and user instructions. It omits error handling details but is otherwise complete.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds context on using a real email for the guest and that phone and message are optional, but does not introduce new parameter details 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 'Request a table at a restaurant' and distinguishes it from a confirmed booking by highlighting that the restaurant is not notified until the user clicks a confirmation link. This 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 provides clear usage context: use a real email, inform the user to check inbox, and notes the 24-hour link expiry. It implicitly advises against treating this as a confirmed booking, though it doesn't explicitly list alternative tools for when a confirmed booking is needed.

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 correctly discloses the temporary nature, non-payment, and automatic expiration. However, it does not specify duration of the hold or any permission requirements, leaving some behavioral 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?

Two efficient sentences: first presents main action and return value, second lists critical caveats. No wasted words. Front-loaded with key information.

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

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

Given 2 parameters, no nested objects, and no output schema, the description covers the essential aspects: what the tool does, its temporary nature, limitations, and when to use alternatives. Lacks details on error conditions or the checkout URL format, 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?

Schema description coverage is 100%, so baseline is 3. The description adds value by stating the max limits per reservation (10 tickets and 10 ticket types), which is not in the schema. This provides useful operational context.

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

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

Clearly states the tool holds tickets and returns a checkout URL. Distinguishes itself from a direct purchase by emphasizing the temporary hold and need for human completion. Contrasts with events sold elsewhere, differentiating from sibling tools like rsvp_event or create_checkout.

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

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

Explicitly says when to use (for events sold directly on this site) and when not (for events via Sympla, Ingresse, Sesc). Also specifies limits of max 10 tickets and 10 ticket types per reservation.

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, description fully discloses critical behavior: RSVP is not immediate, confirmation email sent, link expires in 24 hours, and link is not returned to agent. 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?

Description is concise and front-loaded with purpose, but uses all-caps phrases and multiple sentences that could be streamlined slightly. Still efficient and informative.

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

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

Fully explains the multi-step process, agent's role (tell user), and outcome expectations despite no output schema. Covers all necessary behavioral and usage 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%, so baseline 3. Description adds value by explaining email parameter's purpose (confirmation link sent there) and sourcing event_slug from list_events, but does not cover all parameters in extra detail.

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' with specific verb and resource. Distinguishes from sibling like reserve_event_tickets by emphasizing free events and email confirmation flow.

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

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

Explicitly explains that RSVP requires email confirmation, tells agent to inform user to check inbox, and instructs to use a real address. Provides when-not-to-use context implicitly by explaining the non-immediate process.

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 the full burden. It discloses that the tool searches every menu item, groups results by dish, and returns price, description, dietary labels, and place URL. It also explains the effect of omitting the query. Although it doesn't mention rate limits or auth, the behavioral traits are well-covered 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?

The description is concise with two sentences. It immediately states the main purpose in the first sentence, then elaborates on return structure and query omission behavior. No fluff or 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 no output schema, the description compensates by detailing the return structure (grouped by dish with price, description, dietary labels, place URL). With 2 parameters and simple behavior, the description is complete and covers all essential information for an agent to invoke the tool correctly.

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

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

Schema description coverage is 100%, but the description adds value by providing example query values ('feijoada', 'pizza margherita') and explaining the behavior when query is omitted (lists top dishes). This enriches the parameter understanding beyond the schema.

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

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

The description clearly states the tool's function: 'Find which restaurants serve a dish in this neighborhood.' It specifies the verb (search) and resource (dishes across all restaurants), and provides an example with 'feijoada.' This distinguishes it from siblings like search_places (which searches broader places) and get_restaurant_menus (which returns a specific restaurant's menu).

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 when to use the tool: 'Use this for any "where can I eat X" question.' It also explains the behavior when query is omitted (list top dishes). However, it does not explicitly mention when not to use it or contrast with alternative tools, but the context signals list siblings, and the guidance 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?

The description discloses accent-insensitive and typo-tolerant matching, filter composition (ALL must match), server-side open_now computation, and return fields (open_now, attributes, delivery links, hours). No annotation contradictions. However, lacks rate limits, pagination, or auth requirements.

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 front-loaded with purpose, then efficient details. Every sentence adds value: matching behavior, filter usage, output format, amenity examples. No redundant or extraneous text.

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

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

Given 6 optional parameters and no output schema, the description explains return fields (open_now, attributes, delivery, rating, hours) and their structure (e.g., 'hours: Google Maps periods: day 0=Sun–6=Sat, time HHMM'). Covers common amenity slugs and platform details. Very thorough.

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 100% schema coverage, baseline is 3. The description adds nuance: typo-tolerant examples for 'q', explains filter composition, specifies 'open at this exact moment' for open_now, and lists common amenity slugs. Adds value beyond the schema's property 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 starts with a clear action verb ('Search for places') and specifies the resource ('places in this neighborhood'), distinguishing it from sibling tools like 'get_place' (single place) and 'search_dishes' (specific to 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?

The description provides context on when to use (text search with filters) but does not explicitly exclude other tools or give alternative usage guidance. The 'in this neighborhood' phrase implies location context but no direct comparison to 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?

The description indicates the tool returns a submissionId on success, implying a write operation. Since no annotations are provided, the description carries the burden of disclosure. It does not elaborate on side effects, permissions, or error conditions, which is adequate but not fully transparent.

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

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

Two sentences efficiently convey purpose, prerequisite, and return value. No 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?

For a simple form submission tool with two required parameters and no output schema, the description covers the main usage scenario. It could mention duplicate prevention or validation behavior, but it is sufficiently complete for most use cases.

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?

Both parameters have schema descriptions (100% coverage). The description adds value by providing an example for the fields parameter and reminding the agent to get formId from list_forms, which is helpful beyond the schema.

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

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

The description clearly states the action: 'Submit a form on behalf of the user (Wix Forms)'. It also mentions the prerequisite (list_forms) and the return value, which distinguishes it from sibling tools like 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?

The description explicitly directs the agent to call list_forms first to obtain formId and field keys, providing clear context for use. However, it does not specify when not to use this tool or mention alternatives.

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