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

Without annotations, the description fully discloses that the tool returns a checkout URL, the booking stays off-calendar until payment, and email is not verified at this step. It provides critical behavioral traits beyond the schema.

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

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

The description is somewhat long but every sentence adds value. It is front-loaded with key warnings. Could be slightly more concise without losing information, but it is well-structured.

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

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

Given the complexity (6 params, nested object, no output schema), the description provides essential behavioral context about the checkout flow, preconditions, and limitations. It equips the agent with all necessary information to use the tool correctly.

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

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

Schema coverage is 100% with clear parameter descriptions. The description adds contextual value (e.g., slot format, contact requirements) but does not significantly enhance 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?

The description clearly states it books an appointment slot at a venue, and distinguishes itself from siblings like get_availability and create_checkout by emphasizing that nothing is booked until payment. It specifies the verb and resource precisely.

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

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

The description explicitly instructs to call get_availability immediately before this tool, warns about slot re-validation and rejection, and tells the user they must open the checkout link. This is comprehensive guidance.

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

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

No annotations are provided, so the description carries full burden. It discloses the creation of a checkout URL and the no-login aspect, but does not mention side effects, permissions, or limitations. It adds some value but could be more thorough.

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

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

Two concise sentences, front-loaded with the action. Every sentence serves a purpose with no wasted words.

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

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

The description mentions the output is a checkout URL, but does not specify the exact return format or that the URL is returned in the response. Given no output schema, more detail would help.

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 the items parameter. The description adds 'Wix Stores' context but does not enhance parameter meaning beyond what the schema already provides.

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

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

The description clearly states the tool creates a checkout URL for store products, specifying verb, resource, and domain (Wix Stores). It is distinct from sibling tools, none of which handle 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?

The description provides context that the URL allows the user to complete payment and that no login is needed for the AI agent. It lacks explicit when-not-to-use or alternative tools but 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 carries full burden. It discloses a key behavioral trait: slot times are returned in the venue's timezone, which may differ from the directory's. This is valuable context for correct interpretation of results.

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, using two sentences to convey all essential information without unnecessary words. It front-loads the core purpose and then details parameter usage and behavioral context 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?

Given the tool's simplicity (3 params, no output schema), the description covers what the tool does, how to use parameters, and a critical behavioral note (timezone). It is adequate for correct invocation, though some may desire information about return format.

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

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

Schema coverage is 100% with parameter descriptions, but the description adds meaning: it explains the relationship between serviceId and list_booking_services, reinforces the date format, and emphasizes that place_slug should be consistent. This adds value beyond the schema.

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

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

The description clearly states the tool's purpose: 'Get available time slots for a bookable service on a given date.' It specifies the action ('Get'), resource ('available time slots'), and context ('Wix Bookings'), effectively distinguishing 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 explicit usage guidance: pass serviceId from list_booking_services, date in YYYY-MM-DD, and the same place_slug. It also warns about timezone differences. While it doesn't explicitly state when not to use, the guidance 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?

With no annotations, the description discloses that the tool returns 'ticket names, prices, sale status, and how many are left,' which is adequate for a read operation. It does not mention security or rate limits, but the behavior is clear.

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-loading the purpose and then providing usage and return info. Every word is necessary and no extraneous content.

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

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

Given a simple one-parameter tool with no output schema, the description fully covers what the tool does, what input it needs, and what it returns. It also links to list_events for 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?

The single parameter 'event_slug' is described in the schema as 'Event slug from list_events,' and the description essentially repeats this. With 100% schema coverage, the description adds no extra meaning 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 'Get ticket types and prices for a specific event (Wix Events),' providing a specific verb and resource. It also distinguishes from sibling tools like 'reserve_event_tickets' by focusing on retrieval only.

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

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

The description instructs to pass the event slug from list_events, indicating when to use this tool (after listing events). However, it does not explicitly state when not to use it or mention alternative tools like reserve_event_tickets.

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 fully convey behavior. It discloses return fields but omits potential nuances like error handling (e.g., if no loyalty program exists), required authentication, or rate limits. The disclosure is adequate but not exhaustive.

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

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

Two concise sentences: the first states the purpose, the second details return fields. No redundant words, and key information is front-loaded. The description earns its length.

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

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

With no output schema, the description must explain return values. It lists three key fields (program name, points currency, tier structure), which is sufficient for a simple read tool. However, it doesn't specify the return format (e.g., object) or mention optional fields, leaving minor 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 with 100% coverage. The description correctly adds no parameter information, as none are needed. Baseline for zero-parameter tools is 4, and the description meets this by focusing on return content.

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 'loyalty/rewards program details for this site', with specific fields (program name, points currency, tier structure). This distinguishes it from sibling tools which focus on bookings, events, and other site features.

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 no explicit when-to-use or alternative guidance is given, the context of sibling tools shows none handle loyalty info, so usage is implied when loyalty details are needed. Adding a note about checking for existing loyalty program would improve clarity.

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 full behavioral transparency. It describes the returned data comprehensively (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood), implying a read-only operation. However, it does not mention error handling or authentication 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 a single, concise sentence that efficiently lists all relevant returned fields without unnecessary words. Every element contributes to understanding.

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

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

Given no output schema, the description adequately explains the returned data structure. It lists key fields but does not claim exhaustiveness (uses 'including'). Missing error conditions or auth requirements, but for a simple retrieval tool this is sufficient.

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

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

Schema coverage is 100% with the 'slug' parameter already described. The tool description simply repeats the purpose without adding new semantics beyond what the schema provides. 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 identifies the tool as retrieving full details for a specific place by URL slug, listing key fields like opening hours, open_now, attributes, delivery, ratings, address, and neighborhood. It distinguishes from sibling search_places by focusing on a single known slug.

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

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

The description states when to use (when you have a slug and want full details), but does not explicitly mention when not to use or provide alternative sibling tools. The context of sibling tools like search_places implies the distinction, but explicit guidance is missing.

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

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

No annotations provided, so description carries full burden. It discloses return data (menus, sections, dishes, prices, dietary labels) but does not mention safety, side effects, or authentication 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?

Two sentences, front-loaded with purpose and return data, then prerequisite instruction. No unnecessary words.

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

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

Given 1 parameter and no output schema, description explains return values adequately. Lacks mention of error cases or pagination, but sufficient 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 already covers the parameter (place_slug) with example and source. Description adds only a usage hint that overlaps with schema. With 100% schema coverage, baseline is 3, and no significant additional semantic 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?

The description clearly states 'Get the food menu for a specific restaurant' with a specific verb and resource, and distinguishes from siblings like search_dishes and 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?

Provides explicit prerequisite advice: 'Use search_places or list_categories first to find the restaurant's place_slug.' Clearly guides when to use, though lacks explicit exclusion of 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, and the description only gives basic information about what is returned. It does not disclose pagination behavior, data freshness, permissions, or other behavioral traits beyond the obvious 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 extremely concise: two sentences with no filler. It efficiently conveys the purpose and return values.

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 states the returned fields. However, it lacks details on ordering, error handling, rate limits, or default limit behavior, leaving gaps for a production 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?

Although the schema covers the 'limit' parameter (100% coverage), the description adds value by listing the returned fields (reviewer name, rating, title, content), which is not in the schema. This helps the agent understand the 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 verb ('Get'), the resource ('published reviews'), and specifies the returned fields ('reviewer name, rating, title, and content'). It distinguishes the tool from sibling tools like list_blog_posts or list_products.

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

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

The description implies usage for fetching reviews but does not explicitly state when to use this tool versus alternatives or provide any exclusions or prerequisites.

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

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

With no annotations, the description fully describes the return values (cinema, times, format, language) and a key requirement (movies_enabled). It does not mention rate limits or auth, but the transparency is adequate for a read-only query.

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 sentence states purpose and output, second sentence states a prerequisite. No fluff, every sentence adds value.

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

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

For a simple tool with 2 parameters and no output schema, the description covers purpose, output details, and a prerequisite. It is complete for an agent to understand when and how to use it.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the date default (today BRT) and providing an example for movie_slug. It also clarifies what the output contains beyond the schema.

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

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

The description clearly states the verb 'Get showtimes' and the resource 'for a specific movie at cinemas in this neighborhood, for a given date'. It distinguishes itself from siblings by focusing specifically on showtimes and not other functions like list_movies or 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?

The description includes a prerequisite ('Requires movies_enabled on this site') and implies you need a movie_slug from list_movies. It does not explicitly state when not to use it, but the context is clear enough for appropriate use.

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

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

With no annotations, the description carries the full burden. It discloses the tool is read-only and returns dynamic data (current time and weather). No destructive behavior or side effects are implied. It could mention that no parameters are needed, but the schema already shows that.

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, concise and well-structured. It front-loads the main purpose and then provides specific use cases, with no wasted words.

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

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

Given there is no output schema, the description effectively explains the return values (list of site info fields plus time and weather). It is complete enough for an agent to understand what to expect. It could be slightly richer on the weather format, but it's 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?

There are 0 parameters, and the schema coverage is 100%. The baseline score is 4 since no parameter documentation is needed. The description does not need to add any parameter info.

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

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

The description clearly states that the tool returns basic information about a neighborhood directory, listing specific data types (name, locale, domain, description, canonical URLs, local time, current weather). It distinguishes itself from sibling tools by focusing on site-wide info and contextual time/weather data.

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 provides usage guidance: 'Use this for any "what time is it there" or "what's the weather like" context.' This helps the agent decide when to invoke it. However, it does not mention when not to use it or alternatives, but the narrow scope makes this less critical.

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 clearly states that only published posts are returned and lists the response fields. However, it does not mention ordering, pagination, authentication requirements, or any side effects. The default and max limit are in the schema but not repeated in the description.

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

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

The description is a single sentence that efficiently conveys the tool's purpose and return data. Every word adds value, and there is 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?

Given the absence of an output schema, the description compensates by listing the returned fields, which is adequate for basic usage. However, it omits the response structure (e.g., array of objects), ordering, and error conditions. For a simple list tool with two optional parameters, the completeness is good but not exhaustive.

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% since both parameters have descriptions. The main description does not add additional meaning beyond what the schema provides for 'limit' and 'category'. Thus, the description adds no extra parameter semantics, meeting the baseline of 3.

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

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

The description clearly states the action ('List') and the resource ('recent published blog posts for this site (Wix Blog)'). It lists the returned fields, which distinguishes it from sibling list tools that focus on other entities. However, the term 'recent' is slightly vague without specifying the ordering (e.g., by published date descending).

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives like list_categories or when not to use it. It implicitly states its purpose but lacks 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 provided, so description carries full burden. It discloses that services are listed for all venues (including those without online booking), explains the bookableViaMcp field and its implications for booking, and notes that id is null when not bookable.

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

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

The description is detailed and front-loaded with the most important information. While every sentence is useful, it could be slightly more concise; however, it remains clear and well-structured.

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

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

No output schema, but the description explains the return fields (name, description, price, duration in minutes, bookableViaMcp) and covers edge cases like missing booking system. For a listing tool with one optional parameter, this is extremely 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?

Only one parameter, place_slug. Schema coverage is 100%, but the description adds meaning beyond the schema by explaining it is strongly recommended, what happens with/without it, and its relationship to 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?

The description clearly states the tool lists a venue's services with price and duration. It distinguishes between using place_slug for a specific venue versus omitting it to get directory services, which is a crucial differentiation from sibling tools.

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

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

Provides explicit guidance: use place_slug from search_places for a specific venue; omitting gives directory's services (rare). Also notes that create_booking works only with the place_slug form, a critical usage constraint.

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 communicates that this is a safe, read-only operation. It discloses the return structure (categories, subcategories, labels, etc.), but doesn't mention potential performance constraints or caching behavior. For a simple, parameterless tool, this is sufficient.

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 immediately states the core action and lists the key return elements. Every word adds value, with no redundancy.

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

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

Despite lacking an output schema, the description fully explains what is returned: top-level groups, subcategories, localized labels, schema.org types, and live place counts. For a listing tool with no parameters, this is 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 zero parameters, and the schema coverage is 100%. The description does not need to elaborate on parameters. The baseline score of 4 applies as the tool's simplicity is well-communicated.

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

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

The description clearly identifies the tool's purpose: returning the full category taxonomy of a directory site. It specifies the components included (top-level groups, subcategories, labels, types, place counts), making it distinct from sibling 'list_*' tools that retrieve different resources.

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

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, such as requiring a site context, or scenarios where another tool (e.g., search_places) might be more appropriate.

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 fully discloses behavior: states it returns weatherForecast for events within 7 days, and that 'agora' filter is resolved live on every call with no caching. 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 succinct sentences with clear front-loading of purpose, followed by key behavioral details. No unnecessary words.

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

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

Given no output schema, description adequately explains return fields (date, venue, price, URL, weatherForecast). With 3 optional params and distinct purpose among siblings, it is 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 covers 100% of parameters, baseline 3. Description adds significant value by explaining weather data context and the 'agora' filter's live resolution, beyond schema descriptions.

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

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

Description clearly states 'List upcoming events' with specific fields (date, venue, price, URL) and additional weather data for events within 7 days. Distinct from sibling tools like list_blog_posts or list_offers.

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

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

Explains how to use the 'filter' parameter to narrow results, including live resolution for 'agora'. Does not explicitly mention when not to use or compare to other list tools, but provides clear 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?

No annotations are provided, so the description carries the full burden. It states the tool retrieves data ('Get all FAQ'), implying a read-only operation, but does not explicitly declare its safety profile or any side effects. A clearer statement of read-only behavior would improve this score.

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. The first sentence states the function and structure, the second gives usage guidance. Information is front-loaded and efficient.

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

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

Given no parameters and no output schema, the description is mostly complete: it explains the return content (all FAQs, grouped by category) and usage. It lacks details on potential filtering or pagination, but for a simple list tool, it suffices.

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 schema description coverage is effectively 100%. The description adds context about grouping by category, which is not in the schema. Since no parameters exist, the baseline is 4, and the description meets expectations.

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

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

The description clearly states the tool retrieves all FAQ questions and answers, grouped by category. It explicitly mentions the resource (FAQ) and the action (get all), distinguishing it from sibling tools like list_blog_posts or list_products.

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

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

The description provides explicit usage context: 'Use this to answer common questions about the site — opening hours, parking, policies, etc.' This guides the agent on when to invoke the tool, though it does not explicitly mention when not to use it or list alternative tools.

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

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

With no annotations, the description carries the full burden and clearly discloses the return structure (name, ID, field definitions). It does not discuss pagination or limits, but for a simple list with no parameters, it is sufficiently transparent.

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

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

Two concise sentences, front-loaded with action and return values, 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?

No output schema, so description appropriately explains return values (form name, ID, field definitions). It is 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?

No parameters exist, so baseline score of 4 applies.

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

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

The description clearly states the verb 'List', the resource 'contact/signup forms on this site (Wix Forms)', and specifies the return values (form name, ID, field definitions).

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

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

Explicitly advises using this tool before 'submit_form' to discover fields to fill, providing clear sequential guidance and differentiation from sibling.

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 burden of behavioral disclosure. It states that the tool lists ranked places with editorial notes, but does not mention output format, pagination, or any side effects. For a simple read operation, this 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?

Two sentences that efficiently convey the tool's purpose and usage context without redundancy. 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?

Despite having no output schema, the description adequately covers the tool's function and when to use it. It could mention the output format explicitly, but the context is sufficient for an agent to understand 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 input schema already documents the single parameter 'limit' with description, default, and max. The tool description adds no additional parameter semantics beyond the schema, which is acceptable given 100% schema coverage.

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

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

The description clearly states the tool lists curated editorial guides ('best of' lists) with ranked places and editorial notes. It distinguishes from sibling list tools like list_blog_posts and list_products by specifying the context of local recommendations.

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

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

The description provides clear context on when to use this tool: for 'best X in this neighborhood' questions. It implicitly guides the agent to prefer this tool over others for editorial recommendations, though it lacks explicit not-to-use scenarios.

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

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

With no annotations, the description carries the full burden, and it does well by disclosing the precondition (movies_enabled), the categories included, and the fields returned. It does not mention rate limits or side effects, but for a read-only list tool, the transparency is adequate.

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

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

Two sentences, front-loaded with the main purpose, followed by precise details on what is returned. 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, the description fully explains what the tool returns. It covers the prerequisite, parameter meanings, and output composition. For a simple list tool with 2 parameters, this is 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% and descriptions are already clear. The description adds value by explaining the output fields (title, genres, TMDB rating, runtime, detail URL) and clarifying the meaning of the status categories (e.g., 'now_showing' includes actual showtimes).

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

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

The description clearly states the action ('List') and resource ('movies available in this neighborhood'), distinguishes itself with a precondition ('only on sites with movies_enabled'), and specifies exactly what categories are returned (now-showing, coming-soon, streaming). This is specific and differentiates from siblings like get_showtimes.

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 context (movie listings) but does not explicitly mention when to use this tool vs alternatives like get_showtimes or list_categories. No exclusion criteria or when-not guidance is provided, only a precondition.

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

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

Discloses return fields and special behavior for FLASH offers (countdown deadline). However, with no annotations, it lacks information on side effects, authentication, or rate limits. Adequate but not comprehensive.

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

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

Two clear sentences: first states purpose and outputs, second highlights a key behavior. No filler, front-loaded, and efficient.

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

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

Covers purpose, return fields, and FLASH special case. Missing details on pagination, default sorting, or that only active offers are returned. Relatively complete for a simple 2-param tool with no 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 already describes both parameters (kind enum and limit) with 100% coverage. Description adds only marginal context about FLASH offers, which is redundant with the schema's kind description. 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 and deals, specifies return fields (discount label, promo code, CTA link, validity window, business/place), and distinguishes FLASH offers. The tool name and context differentiate it 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?

No guidance on when to use this tool versus alternatives like list_events or list_products. Does not specify when not to use it or any prerequisites.

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

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

No annotations provided, but description discloses what the tool returns (plan name, description, price, etc.) and the two behavioral modes. Does not explicitly state it's read-only, but behavior is well-covered for a listing tool.

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

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

Three sentences conveying purpose, primary use case, and return fields. No redundant information, efficient and 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?

For a simple listing tool with one optional parameter, the description fully covers functionality, usage context, return data, and practical guidance. No missing aspects.

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 one parameter, place_slug, with 100% schema coverage. The description adds significant context beyond the schema by explaining the difference between providing it or not and recommends its use.

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 lists membership/subscription plans, distinguishes between listing venue-specific plans (with place_slug) and directory's own plans (without). The verb 'list' is appropriate and the tool is distinct from 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?

Explicitly recommends passing place_slug from search_places as the primary use case, warns that omitting it yields directory's own plans which most sites lack. Clear when-to-use and 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 provided, the description must fully convey behavioral traits. It states the tool lists products and returns specific fields, implying a read-only operation. However, it fails to mention pagination behavior (though 'limit' is in schema), ordering, or any side effects. The description is functional but lacks depth expected for an unannotated 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, clear sentence with no filler. It front-loads the key action (List products) and efficiently communicates the return fields. No unnecessary information is present.

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 is a simple list with no output schema and no annotations, the description covers the basic purpose and return fields. However, it does not mention pagination details (beyond the limit parameter in the schema) or any ordering, which would enhance completeness for an agent. Still, it is mostly adequate.

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

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

Schema coverage is 100%, so the baseline is 3. The description does not add any additional meaning to the parameters beyond what the schema already provides (q and limit are clearly described in the schema). No extra value is contributed by the description for parameter understanding.

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

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

The description clearly states the verb 'List' and the resource 'products in this site's store (Wix Stores)', and specifies the returned fields (name, price, stock status, product type). This distinctly differentiates it from sibling list tools like list_blog_posts and list_categories.

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., list_categories, list_offers). It does not mention prerequisites, filtering behavior beyond the optional 'q' parameter, or when not to use it. Usage context is only implied.

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

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

With no annotations, the description carries the burden. It discloses the scope and return fields (name, URL, category, metadata). It doesn't cover pagination or sorting but is adequate for a list 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 verb and resource, then details. No redundant words, efficient and clear.

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 of the tool (one optional parameter, no output schema), the description covers the essential return fields and distinguishes from sibling lists. Slightly vague about 'any available metadata' but overall sufficient.

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

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

Schema coverage is 100% for the only parameter (limit), so baseline is 3. The description adds no additional parameter-specific meaning beyond what the schema already provides.

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

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

The description clearly states the tool lists 'solo service-provider profiles' and distinguishes from siblings by specifying 'businesses without a fixed physical location' with examples.

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 but no explicit when-to-use or comparisons to sibling tools. It implies usage for solo service providers without location but lacks guidance on 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 fully disclose behavior. It does so comprehensively: the restaurant is not notified yet, a confirmation email with a link is sent, the link expires in 24 hours, and this is a request not a confirmed booking. These are critical behaviors beyond the schema.

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

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

The description is relatively concise given the amount of critical information conveyed. It is front-loaded with the main purpose. However, it slightly repeats schema descriptions (e.g., email, requestedAt) which could be trimmed to be more efficient.

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

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

Given the tool has 7 parameters and no output schema, the description covers the workflow well, explaining the asynchronous nature and the need for user action. However, it does not describe what the tool returns (e.g., a request ID), which is a minor gap for completeness.

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

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

The schema has 100% description coverage, so the baseline is 3. The description does not add new semantic information beyond what the schema already provides for each parameter; it only reiterates some details (e.g., email gets link, requestedAt must be future). Thus, no additional 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?

The description clearly states 'Request a table at a restaurant' and distinguishes itself by emphasizing it is a request, not a confirmed booking, which differentiates it from siblings like 'create_booking'. It specifies the exact workflow: the restaurant is not notified until the confirmation link is clicked.

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 guidance on when to use this tool (for requesting a table) and warns about the non-confirmed nature. It instructs to tell the user to check their inbox and use a real email address. It implicitly contrasts with confirmed booking tools but does not explicitly list when not to use it or name 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 provided, the description fully discloses that the hold is temporary, nothing is paid, the hold expires, and the tickets are not reserved until checkout is completed. This provides clear behavioral expectations.

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

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

Two sentences, no wasted words. The first sentence states the primary action, and the second sentence contains all critical caveats in a clear, highlighted manner (using caps).

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

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

Despite no output schema, the description explains it returns a checkout URL. It covers prerequisites, constraints, and exclusions. The tool is straightforward and the description addresses all necessary 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 is 3. The description adds value by specifying the maximum quantities (10 tickets and 10 ticket types), which is not in the schema. It also references related tools (get_event_tickets, list_events) for obtaining parameter values.

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 sold through Wix Events and returns a checkout URL. It uses a specific verb ('Hold tickets') and resource ('event sold through this site'), distinguishing it from sibling tools like create_booking or request_reservation.

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

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

Explicitly provides when-to-use (event sold through this site) and when-not-to-use (events sold elsewhere like Sympla, Ingresse, Sesc), and names the alternative (use the event's own ticketUrl). Also states constraints (max 10 tickets and 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 behavior: no immediate guest list entry, email-based confirmation, 24-hour link expiry, and the need to inform the user. There are no contradictions or omissions.

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 with no fluff. Key information is front-loaded, and every sentence adds essential guidance. It is appropriately sized for the tool's simplicity.

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 or annotations, the description covers the RSVP flow, user expectations, and behavioral constraints. It is complete for a tool with 4 required parameters and straightforward behavior.

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 does not add meaning beyond the schema; each parameter's description in the schema is identical to the tool description's mentions. No extra context is provided for parameters.

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 is for RSVPing to a free event on Wix Events, using specific verb 'RSVP' and resource 'free event'. It distinguishes from sibling tools like reserve_event_tickets, which handle paid ticketed events.

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

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

The description explains the asynchronous flow (confirmation email, link expiry, user must check inbox) and mandates using a real address. It lacks explicit comparison to sibling tools but the context of free vs paid events is implied.

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

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

No annotations provided, but description discloses behavior: searches all menus across restaurants, groups by dish, returns price/description/dietary labels/URL. Implies read-only, no destructive effects. Transparent about output structure.

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. Purpose is front-loaded. Efficient and clear.

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

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

No output schema, but description covers return values (price, description, dietary labels, URL). With two well-described parameters and clear purpose, it is sufficiently complete for a 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%, baseline 3. Description adds value by explaining query is a dish name and that omitting it lists top dishes. Also explains limit defaults and max, supplementing schema.

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

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

Description clearly states the tool finds restaurants serving a dish, with specific verb and resource. It distinguishes from siblings like search_places by focusing on dish-level search. Example query 'feijoada' makes it concrete.

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 use for 'where can I eat X' questions. Mentions omitting query to list top dishes, giving clear usage context. Does not explicitly state when not to use, but clues are sufficient.

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

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

With no annotations, the description carries full burden and discloses key behaviors: accent-insensitive and typo-tolerant matching, relevance ranking, precomputed open_now, filter semantics, result structure (delivery links, hours format). It does not cover pagination or rate limits, but otherwise 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?

Description is concise, front-loaded with purpose, and each sentence adds value. No wasted words. Well-structured for quick comprehension.

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

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

For a search tool with 6 parameters and no output schema, the description covers query behavior, filters, result fields (open_now, attributes, delivery, rating, hours), and amenity slugs. It lacks pagination details and error handling, but is largely 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%, and description adds meaning beyond schema: explains typo tolerance for 'q', server-side computation for 'open_now', lists common slugs for 'attributes', and mentions case-insensitive substring match for 'category' and 'neighborhood'.

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

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

The description clearly states the tool searches for places like restaurants and cafes in a neighborhood, using a specific verb ('Search') and resource ('places'). It distinguishes itself from sibling tools like 'get_place' (single place) and 'search_dishes' (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?

Usage is implied through description of filters and matching behavior, but there is no explicit guidance on when to use this tool versus alternatives. Given many siblings, lack of when-not-to-use is a gap.

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. Mentions it returns 'submissionId on success' but doesn't disclose side effects, authorization needs, error handling, or idempotency.

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 clear front-loading: purpose first, then prerequisite, then return value. No superfluous 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 simple tool with 2 required params and no output schema, description sufficiently covers inputs and output. Could add error handling info but adequate for typical 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 description coverage is 100%. The description adds practical context with an example of key-value pairs matching list_forms, enhancing understanding beyond the schema.

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

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

Description clearly states 'Submit a form on behalf of the user (Wix Forms)' with a specific verb and resource, distinguishes from sibling tools like list_forms by providing a prerequisite workflow.

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

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

Explicitly instructs to 'Call list_forms first to get the formId and field keys', providing clear prerequisite and usage context, though lacks explicit when-not-to-use scenarios.

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