Aclimação

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

With no annotations, the description fully bears the burden of disclosing behavior. It clearly states that the booking is not finalized until payment via a checkout URL, the slot stays off the calendar, and the contact email is not verified. This is comprehensive and prevents agent confusion.

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, dense paragraph with no wasted words. Key points are front-loaded: purpose, critical caveat (payment required), and workflow steps. 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 the complexity (6 parameters, nested contact object, no output schema), the description covers the entire workflow: pre-requisite step (get_availability), the booking action, post-action (user must pay), and essential caveats (slot re-validation, email not verified). It is complete for an agent to use 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%, so the baseline is 3. The description adds value by linking place_slug to search_places, serviceId to list_booking_services, and startDate/endDate to get_availability, but does not deeply elaborate on parameters beyond the schema descriptions.

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

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

The description clearly states the tool's purpose: 'Book an appointment slot at a venue (Wix Bookings).' It also immediately clarifies that nothing is booked until payment, distinguishing it from a direct booking tool. This specificity helps the agent select it among siblings like 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?

The description explicitly instructs to 'Call get_availability immediately before this' and explains why (slot re-validation). It also tells the agent to inform the user to open the checkout link. While it doesn't list when not to use it, the context is clear and actionable.

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

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

Describes core behavior: creates URL, user clicks to pay, no login needed. No annotations provided, so description carries full burden, but lacks details on side effects or output.

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

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

Two concise sentences with no wasted words, front-loading the key action and context.

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

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

Simple tool with one parameter; lacks return value description (the URL) which is crucial for invocation. No output schema exists.

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 minimal extra meaning beyond the schema—just reaffirms 'one or more' and product 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 verb 'create', resource 'direct checkout URL', and scope 'one or more store products (Wix Stores)'. Distinct from siblings 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?

Implies usage when no user login is needed on the AI agent side, but no explicit when-to-use or when-not-to-use compared to other tools.

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

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

With no annotations, the description carries full burden. It discloses that slot times are returned in the venue's timezone, which is a critical behavioral detail. It implies read-only access but does not discuss error handling or performance 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?

Two sentences, front-loaded with purpose, no fluff. Every sentence adds value: purpose, required parameters, and a crucial timezone warning.

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 3 parameters, the description covers purpose, required inputs, and a key behavioral trait (timezone). It does not describe return format or edge cases like no availability, but this is acceptable for a simple query 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 3. The description adds workflow context (using serviceId from list_booking_services, same place_slug) but does not add new semantic meaning beyond the schema descriptions. The timezone note is about output, not 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 retrieves available time slots for a bookable service on a given date, specifying the domain (Wix Bookings) and linking to a sibling (list_booking_services). This distinguishes it from other siblings like create_booking or get_event_tickets.

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

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

The description gives explicit instructions: pass serviceId from list_booking_services, date in YYYY-MM-DD, and the same place_slug. It warns about timezone differences. However, it does not explicitly state when not to use this tool or mention alternative tools like create_booking for making bookings.

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

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

No annotations are provided, so the description carries full burden. It mentions the tool returns ticket data but doesn't explicitly state it's read-only or disclose any side effects. For a simple query tool, this is adequate but not comprehensive.

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

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

The description is concise—two sentences that front-load the purpose and include key details without redundancy. Every sentence contributes value.

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

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

The tool has one parameter and no output schema. The description explains what is returned, making it sufficient for an agent to use correctly. Slightly more detail on availability or sale status format could improve completeness.

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

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

Schema coverage is 100% with one parameter documented. The description adds value by explaining that event_slug comes from list_events, providing context beyond the schema's description.

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

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

The description clearly states the tool gets ticket types and prices for a specific event, specifying it's for Wix Events and listing the returned data (names, prices, sale status, quantity). It distinguishes itself from siblings like list_events (which lists events) and reserve_event_tickets (which reserves).

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, providing a clear prerequisite. However, it doesn't explicitly state when not to use this tool or mention alternatives like reserve_event_tickets for next steps.

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

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

With no annotations, the description must disclose behavior. It indicates a read operation by noting 'returns' but does not explicitly state it is read-only, idempotent, or free of side effects. No mention of permissions or error cases.

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, front-loaded with the purpose, and contains no extraneous information. Every word adds value.

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

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

Given zero parameters and no output schema, the description sufficiently explains the return value. However, it could mention that it retrieves the current program details for the site and that it is safe to call without side effects.

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

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

There are zero parameters, so schema coverage is 100%. The description adds context about what the tool returns, which is meaningful for a parameterless tool.

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

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

The description clearly states the verb 'Get' and the resource 'loyalty/rewards program details'. It specifies the site context (Wix Loyalty) and lists key return fields (program name, points currency, tier structure), distinguishing it from sibling tools like 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 implies the tool is for retrieving loyalty program details, but it does not explicitly guide when to use this over alternatives. No mention of when not to use or comparison with siblings like get_site_info.

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

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

No annotations are provided, so the description carries full burden. It states that details are returned and lists fields, but does not disclose error handling, authentication needs, or any side effects. Adequate for a simple read operation 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?

A single, well-formed sentence that front-loads the purpose and efficiently lists included data. No unnecessary words or 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?

For a simple single-parameter tool without output schema, the description covers the main purpose and return data. Minor gaps: no mention of invalid slug handling or distinction from sibling speciality detail tools (e.g., get_reviews).

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% (slug parameter described both in schema and description). The description adds an example and context (URL slug) but does not significantly enhance beyond what the schema already provides. Baseline score of 3 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 specifies the verb 'Get full details' and the resource 'specific place', and distinguishes it from siblings like search_places by requiring a URL slug and listing included data (opening hours, ratings, address, neighborhood).

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

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

Implied usage: when you have a URL slug. No explicit when-to-use or when-not-to-use compared to alternatives like search_places or get_reviews, leaving the agent to infer 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 present, so the description bears full responsibility. It reveals the tool is read-only by describing returned data, but omits details like error handling, rate limits, or authorization needs. The disclosure is adequate but not comprehensive.

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

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

The description is two sentences long, front-loading the core purpose and immediately following with prerequisite usage. Every sentence is essential, with 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?

Given the tool's simplicity (one parameter, no output schema, no nested objects), the description adequately covers what the tool returns and how to prepare. It could mention potential errors (e.g., invalid slug) 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?

The single required parameter 'place_slug' is well-explained in both the input schema and description, with an example ('bar-do-ze') and source (search_places or place URL). Schema coverage is 100%, and the description adds clarity without redundancy.

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

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

The description clearly states the tool retrieves a restaurant's food menu, specifying it returns sections, dishes, descriptions, prices, and dietary labels. It distinguishes itself from sibling tools like search_dishes by targeting a specific restaurant's full 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 instructs users to first use search_places or list_categories to obtain the place_slug, providing clear pre-usage steps. It does not explicitly mention when not to use this tool, but the guidance is adequate for correct invocation.

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 that the tool reads published reviews and returns specific fields. It does not mention potential errors, authentication needs, or default ordering, but for a simple read operation, 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?

The description is one concise sentence that front-loads the purpose and includes return value details. Every word is necessary 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?

Given a simple operation with one optional parameter and no output schema, the description is nearly complete. It could mention default sort order or that only published reviews are returned, but it is sufficient for agent understanding.

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

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

Schema coverage is 100% for the single parameter 'limit', with full description in the schema. The tool description adds no additional meaning to the parameter beyond what the schema provides, so baseline 3 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 tool retrieves published reviews for the site, specifying the returned fields (reviewer name, rating, title, content). The verb 'Get' and resource 'reviews' are explicit. No sibling tool conflicts as there is no other review 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 provides clear context that the tool is for reading reviews, but does not explicitly state when to use or not use alternatives. Since it is the only review-related tool, usage is implied, but a small gap exists for explicit 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 bears full responsibility. It discloses that it returns session times, format, and language, and mentions a prerequisite. However, it does not describe error behavior (e.g., when no showtimes are found), rate limits, or timezone handling beyond noting BRT for default date.

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

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

Two sentences, front-loaded with the main action. No wasted words. Every sentence adds necessary information.

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

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

For a simple read tool with 2 parameters and no output schema, the description covers the core behavior (returns cinema, times, format, language) and a prerequisite. No return structure is detailed, but the key result fields are mentioned. This is adequate but could briefly note sorting or edge 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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the movie_slug provenance ('from list_movies') and the date format (YYYY-MM-DD). This context aids the agent in parameter selection 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', the resource 'showtimes', and the context: for a specific movie at cinemas in this neighborhood for a given date. It distinguishes itself from sibling tools like list_movies, which lists movies, and doesn't overlap with booking/reservation tools.

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

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

The description provides a clear prerequisite: 'Requires movies_enabled on this site.' It implies usage after list_movies to get the movie_slug. However, it does not explicitly state when not to use the tool or provide comparisons to 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?

Since no annotations are provided, the description carries full burden. It discloses that the tool returns dynamic data (local time and current weather), which is behavioral. It does not mention any side effects or authorization, but for a read-only, parameterless 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?

The description is a single sentence that efficiently conveys all necessary information without fluff. It could be slightly improved by splitting into two sentences for readability, but it is already concise and 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?

Given no output schema and no parameters, the description fully explains what the tool returns. It covers all key aspects an agent needs to decide to call it: basic site info, time, and weather. The provided use cases also add 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?

There are no parameters, so schema coverage is 100%. The description adds significant value by listing the exact fields returned (name, locale, domain, description, canonical URLs, local time, weather), which is beyond the baseline of 4 for zero 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 returns basic site info including name, locale, domain, description, canonical URLs, local time, and weather. It provides specific examples of when to use it ('what time is it there' or 'what's the weather like'), effectively differentiating it from sibling tools like get_place or search_places.

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

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

The description explicitly states the contexts for using the tool (time and weather queries). While it does not mention when not to use it or list alternatives, the given usage guidance is clear and sufficient for a tool with no parameters.

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

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

No annotations exist, so the description carries full burden. It mentions return fields and the scope ('this site'), but does not disclose ordering (e.g., by published date descending), authentication needs, rate limits, or whether only published posts are listed. The read-only nature is implied but not explicit.

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

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

The description is two concise sentences: first states the purpose, second lists return fields. No redundant words, front-loaded with main action.

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

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

For a simple list tool with two optional parameters and no output schema, the description covers the essential: what it returns and the scope. Lacks mention of ordering or pagination details, but is adequate for the simplicity level.

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% (both parameters have descriptions). The tool's description does not add extra meaning beyond the schema; it simply repeats the notion of categories in the return list. Baseline of 3 is appropriate.

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

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

The description clearly states the tool lists recent published blog posts for a Wix site, specifying the resource and action. It distinguishes from sibling list tools (e.g., list_products) by being specific to blog posts.

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

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

The description provides no guidance on when to use this tool vs alternatives, no prerequisites, and no exclusion criteria. Sibling tools exist for other resources but no comparison or selection hints are given.

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

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

No annotations provided, so description carries full burden. Discloses that services are listed for every venue including those without online booking, and explains the bookableViaMcp flag's meaning. Does not mention pagination or rate limits, but adds useful context beyond a simple 'list services'.

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 well-structured, starting with purpose then parameter and return details. However, it is slightly verbose with some explanatory asides (e.g., 'that is what you want in almost every case') that could be trimmed.

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 sufficiently explains return fields (name, description, price, duration, bookableViaMcp) and caveats (null id when not bookable). Does not cover error handling or ordering, but adequate for a simple list tool.

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

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

Only one parameter (place_slug) with 100% schema coverage; schema description already explains its purpose. Description adds context about typical usage and the directory's own services, but not significantly more than 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 it lists a venue's services with price and duration. It distinguishes between listing venue services (with place_slug) and directory services (without), which differentiates it from sibling tools like search_places or create_booking.

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

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

Explicitly says when to use it: pass place_slug from search_places for typical venue service listing. Discusses the alternative (omitting place_slug) and notes it's rarely applicable. Does not explicitly state when not to use, but the sibling list implies other tools for different actions.

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 transparency burden. It indicates a read operation (returns) and describes the output contents. However, it does not disclose potential size or performance implications of the full taxonomy.

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 lists all key output elements efficiently. No wasted words.

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

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

Given the tool has no parameters and no output schema, the description provides a reasonable overview of the return value. It is missing details about output format or any pagination, but still adequate for understanding the tool's function.

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, so there is nothing to add. The description correctly does not attempt to describe nonexistent parameters, and the 100% schema coverage baseline of 3 is exceeded because the description adds value in explaining 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 it returns the full category taxonomy with specific components (top-level groups, subcategories, labels, schema.org types, place counts). This distinguishes it from sibling tools that focus on other entities like bookings, places, or events.

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

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

The description does not explicitly state when to use this tool versus alternatives like list_products or list_offers. Usage is implied by the tool's name and description, but no guidance on when not to use it or what distinguishes it from similar list tools.

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

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

Discloses that events within 7 days include weatherForecast and that 'agora' filter is resolved live (no caching), providing useful behavioral context beyond the schema. With no annotations, this carries the full burden.

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 front-loaded purpose, no redundant text. The second sentence is slightly long but still efficient. Good structure overall.

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 key aspects like returned fields, filter behavior, and weather data, but could mention ordering or pagination details. Given no output schema, it provides enough context for an agent.

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

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

Schema coverage is 100%, so baseline is 3. The description adds significant value by explaining filter values in detail (e.g., exclusion of season runs for 'agora'), enhancing understanding 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?

The description clearly states the verb 'list' and the resource 'upcoming events', and specifies returned fields (date, venue, price, URL), distinguishing it from sibling tools that handle other resources like movies or bookings.

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 on using the `filter` parameter with examples (e.g., 'agora' for live events), helping the agent decide when to use this tool, but does not explicitly exclude alternatives like get_event_tickets or rsvp_event.

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 present, so the description carries full burden. It discloses that results are grouped by category, which is a key behavioral trait. No mention of auth or side effects, but as a read-only list tool, this is acceptable.

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

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

Two sentences, front-loaded with the core action and result, plus usage example. 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 zero parameters and no output schema, the description fully covers what the tool does, what it returns (grouped Q&A), and why to use it. No gaps.

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

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

The input schema has zero parameters with 100% coverage, so baseline is 4. The description adds no parameter info but does not need to; it clarifies what data is returned (questions, answers, grouped).

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

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

The description specifies the verb 'Get' and the resource 'all FAQ questions and answers' for the site, grouped by category. It clearly distinguishes from sibling list tools by focusing on FAQs for answering common questions.

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

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

The description states 'Use this to answer common questions about the site' but does not provide explicit when-not-to-use or alternative tools. Usage is implied but not comprehensive.

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 responsibility. It discloses the return values (form name, ID, field definitions) and the listing nature of the operation. It could explicitly state that the operation is read-only and non-destructive, but the context (no parameters, list verb) makes this implicit.

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, zero waste. The first sentence states the action and resource, the second adds usage context and return details. Information is front-loaded 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?

For a simple list tool with no parameters and no output schema, the description provides all necessary context: what it lists, what it returns, and how to use it in conjunction with a sibling tool. 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?

The input schema has no parameters (0 parameters, 100% coverage), so the description does not need to add parameter information. 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?

Description explicitly states the verb 'list' and the resource 'available contact/signup forms' on this site (Wix Forms). It also specifies what is returned: form name, ID, and field definitions. This distinguishes it from sibling tools like submit_form, which is explicitly referenced.

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

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

The description clearly states when to use the tool: 'Use before submit_form to discover which fields to fill.' It implies usage context but does not provide explicit alternatives or when-not-to-use scenarios beyond this. However, the reference to submit_form is helpful.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description implies a read-only operation, but does not mention any auth requirements, rate limits, or other behavioral traits. This is a significant 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 with no fluff. It efficiently communicates the tool's purpose and a key use case.

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 input schema with one optional parameter and no output schema, the description covers the main functionality. However, the lack of behavioral transparency reduces 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% coverage for the single parameter 'limit', but the description adds context about the returned content (ranked places with editorial notes), which goes beyond the schema's description.

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

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

The description clearly states the tool lists curated editorial guides with ranked places and editorial notes, distinguishing it from other list tools like list_blog_posts. It also provides an example use case, making the purpose highly specific.

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

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

The description explicitly positions this tool as the best source for 'best X in this neighborhood' questions, giving clear context for when to use it. However, it does not mention when not to use it or explicitly name 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 full burden. It discloses important behaviors: only works on sites with movies_enabled, returns now-showing, coming-soon, and streaming films, and includes specific fields. However, it does not mention rate limits or authentication needs, which is acceptable 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 with no wasted words. The first sentence states the core purpose; the second lists what is returned. 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 output schema, the description adequately explains return fields (title, genres, TMDB rating, runtime, detail URL) and the conditional behavior (movies_enabled). It covers all necessary aspects for a list tool with two parameters.

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

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

Schema coverage is 100% with detailed parameter descriptions, so baseline is 3. The tool description adds context about what the returned statuses mean (e.g., 'now-showing films with showtimes at local cinemas'), but does not significantly expand 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 'List movies available in this neighborhood (only on sites with movies_enabled)', specifying the exact resource (movies) and action (list). It distinguishes from sibling tools like list_events or list_blog_posts by focusing on movies.

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

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

The description does not explicitly provide when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The usage is implied (use for listing movies), but no comparative guidance is given.

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

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

No annotations provided, so description carries full burden. Discloses return fields and FLASH countdown deadline, but lacks info on idempotency, rate limits, or handling of empty 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?

Two sentences, front-loaded with purpose, 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?

No output schema; description covers return fields. But missing details on pagination, ordering, and definition of 'active'. Adequate but not 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. Description adds context for kind parameter by explaining FLASH meaning, but does not enhance limit parameter 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?

States specific verb 'List' and resource 'active promotions and deals', clearly distinguishing from sibling list tools (e.g., list_blog_posts, list_events). Mentions return fields and special FLASH 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?

No guidance on when to use this tool vs. other list tools. Does not mention exclusions or context for using list_offers over alternatives.

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

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

No annotations are provided, so the description must disclose behavioral traits. It mentions the output fields and that it lists plans, implying a read-only operation. However, it does not explicitly state that it is safe (non-destructive), requires authentication, or has rate limits. It lacks depth beyond listing the return values.

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

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

The description is a single sentence that is front-loaded with the action and resource, followed by the return values. It is concise 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?

For a simple list operation with no parameters, the description covers the purpose and return fields adequately. It lacks output schema but explains the return content. It could mention pagination or sorting but that is not critical for a basic list.

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, so baseline is 4. The description adds no parameter details but reinforces that no inputs are needed. This is adequate given no parameters exist.

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

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

The description explicitly states the tool lists membership/subscription plans offered by Wix Pricing Plans. It specifies the returned fields (name, price, billing cycle, perks, checkout URL). This clearly distinguishes it from sibling tools like list_products or list_events.

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

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

The description explains what the tool does but provides no guidance on when to use it over alternatives or any prerequisites. Usage is implied by the listing nature, but explicit when-to-use or when-not-to-use 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns specific fields, indicating a read operation, but lacks details on pagination, sorting, authentication requirements, or potential side effects. The minimal disclosure leaves important behavioral traits undocumented.

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

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

The description is a single sentence that is front-loaded with the verb and resource. Every word contributes to clarity without redundancy or unnecessary detail. It is optimally concise.

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 two optional parameters and no output schema, the description adequately conveys the purpose and return fields. However, it could improve by clarifying that it returns a list (implied) or mentioning default/sorting behavior, but the current content is largely sufficient.

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

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

Schema description coverage is 100%, meaning the input schema already documents both parameters (q and limit). The description adds no extra meaning beyond the schema's descriptions, so it meets the baseline but provides 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 the tool lists products in the Wix Stores site and specifies return fields (name, price, stock status, product type). It distinguishes from sibling tools that list other entities (blog posts, categories, etc.) by name and context, though it does not explicitly differentiate.

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

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

The description implies usage context (listing products in a store) but provides no explicit guidance on when to use this tool versus alternatives (e.g., list_categories) or any prerequisites. The name and sibling set make the intended use clear, but no exclusions or conditions are mentioned.

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

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

With no annotations, the description carries full burden. It does not mention that the operation is read-only, idempotent, or free of side effects. It only describes the output fields, not behavioral aspects like pagination or rate limits.

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

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

Two sentences: the first states the action and resource with examples; the second lists returned fields. No fluff, front-loaded, and 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?

The description explains what profiles are listed and what fields are returned, but lacks information on default limit, pagination, sorting, or whether the list is exhaustive. Given simplicity, it is adequate but not complete.

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

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

The input schema provides 100% coverage for the only parameter (limit) with its own description. The tool description adds no additional meaning about parameters, so baseline 3 is appropriate.

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

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

The description clearly states it lists 'solo service-provider profiles' with specific examples (dog walkers, tutors). It distinguishes from other list tools by specifying the type of profiles and the returned fields (name, URL, category, metadata).

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

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

The description does not explicitly state when to use this tool over siblings. It only describes what it lists, leaving the selection to the user's inference from the resource type.

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 thoroughly explains the asynchronous nature: the request is held, a confirmation email is sent, the restaurant is only notified after the link is clicked, and the link expires. It also states that the confirmation link is not returned to the agent, which is critical for the AI to understand its limitations.

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 paragraph that efficiently conveys all critical information. It is front-loaded with the purpose. While it is concise, a slight restructuring could improve readability, but overall every sentence serves a purpose.

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

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

Given the tool has 7 parameters, no output schema, and no annotations, the description adequately covers the workflow and behavioral nuances. It explains the request-hold-confirm process and user actions needed. However, it does not cover error conditions or edge cases (e.g., invalid email), which could be useful for an AI agent.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond the schema: it clarifies that the email gets the confirmation link and that place_slug comes from search_places. However, it does not add syntax or format details that significantly enhance 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 'Request a table at a restaurant' with a specific verb and resource. It distinguishes itself from a confirmed booking by emphasizing this is a request, not a booking, which differentiates it from sibling tools like create_booking.

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

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

The description explicitly tells the user when to use this tool (to request a table) and what to expect: the restaurant is not notified yet, a confirmation email is sent, the user must check their inbox, and the link expires in 24 hours. It also instructs to use a real email address. This provides clear guidance on usage and 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 fully discloses the temporary nature, expiration, no payment, max limits, and scope. This is thorough behavioral transparency.

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

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

Three sentences, front-loaded with main action, no wasted words. Efficiently 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?

Mostly complete given tool simplicity. Lacks mention of error conditions or what happens on failure, but purpose and limits are clear. Return value (checkout URL) is mentioned.

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

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

Schema coverage is 100%, but description adds cross-references: event_slug from list_events, ticketDefinitionId from get_event_tickets, and notes max 10 per reservation. This adds value beyond the schema's basic descriptions.

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

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

The description clearly states it holds tickets temporarily and returns a checkout URL. It distinguishes from siblings like 'create_booking' or 'create_checkout' by emphasizing it's a hold, not a payment.

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 when to use (events sold through this site) and when not to (events sold elsewhere via Sympla, Ingresse, Sesc, use ticketUrl). Also mentions max limits of 10 tickets and 10 ticket types.

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

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

No annotations exist, so description carries full burden. It discloses the asynchronous confirmation process, email expiry, and that the link is not returned. Lacks mention of rate limits or consequences of fake emails, but covers essential behavioral traits.

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

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

Two sentences with no fluff. Front-loaded with purpose, immediately followed by critical behavioral details. Every sentence serves a purpose.

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

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

Given no output schema and simple inputs, the description covers the RSVP workflow, agent instructions, and key constraints. Missing error handling details or success feedback, but overall adequate for 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%, so baseline is 3. Description adds context for email ('the confirmation link is sent here') and event_slug ('from list_events'), but firstName and lastName descriptions are minimal. Adds some value but not significant.

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

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

The description clearly states 'RSVP to a free event on this site (Wix Events)' using a specific verb and resource, and effectively distinguishes from sibling tools like reserve_event_tickets for paid 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?

Explicitly guides when to use (free events only), warns that no guest is added immediately, instructs agent to tell user to check inbox, and advises using a real email address. No mention of alternatives but context makes it clear.

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

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

With no annotations, the description fully discloses behavior: searches all menu items across all restaurants, groups by dish, and returns structured details. It covers both query and no-query modes. Missing details like pagination or error handling are minor.

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-load the purpose and provide actionable details without superfluous text. Every word earns its place.

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

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

The description fully explains the tool's functionality and output for a search tool without an output schema. It covers both query modes but lacks error handling details, which is acceptable for this complexity.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining 'query' as a dish name and 'limit' defaults (20, max 50), enhancing the schema's descriptions.

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

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

The description clearly states the tool finds which restaurants serve a dish, with an explicit example ('feijoada') and output details (price, description, dietary labels, URL). It distinguishes itself from sibling tools by focusing on dish search across 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 states to use this for 'where can I eat X' questions and explains query omission behavior. While it doesn't list exclusions or alternatives, the sibling context makes usage clear.

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

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

Discloses accent-insensitive, typo-tolerant search, relevance ranking, and opening hours format. No annotations provided, so description carries the burden effectively.

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

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

Concise, front-loaded with purpose, each sentence adds value, no wasted words.

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

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

Explains opening hours format but does not describe the overall result structure (e.g., other fields returned per place), leaving some gaps for an agent.

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

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

Adds behavioral meaning beyond schema (e.g., 'accent-insensitive and typo-tolerant' for q, 'case-insensitive substring match' for category/neighborhood), despite 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?

Clearly states it searches for places with examples (restaurants, cafes, shops), distinguishing it from sibling tools like get_place or search_dishes.

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

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

Implies usage for finding places in a neighborhood with optional filters, but lacks explicit guidance on when not to use it or compare with alternatives.

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

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

No annotations provided, so description carries full burden. States it submits on behalf of user (write operation) and returns submissionId. Lacks details on side effects, idempotency, or error conditions, but adequate for a simple tool.

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

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

Two sentences, front-loaded with purpose, then prerequisite and return. Every sentence adds necessary information without redundancy.

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

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

Given 2 parameters, no output schema, and no annotations, the description covers purpose, prerequisite, return value, and an example. Lacks error handling details but is reasonably complete for form submission.

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

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

Schema coverage is 100% (both parameters described). Description adds value by explaining fields as key-value pairs matching list_forms keys and provides an example, which clarifies usage beyond the schema.

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

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

The description clearly states the verb 'Submit' and the resource 'a form on behalf of the user (Wix Forms)', distinguishing this tool from siblings like list_forms. It also mentions the return value (submissionId).

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

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

Explicitly instructs to call list_forms first to obtain formId and field keys, providing a clear prerequisite. Does not explicitly state when not to use, but the guidance is strong.

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