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

No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, or rate limits. The term 'live stock' implies real-time data but lacks depth.

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

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

The description is extremely concise with two short sentences. Every word serves a purpose, starting with the core function and then providing usage advice. 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?

With no output schema, the description fails to explain what the response contains (e.g., structure of availability data). For a simple tool it's acceptable but leaves the agent guessing 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% for the single parameter 'slug', documented as 'Slug del evento'. The description adds no additional meaning beyond what the schema already provides, meeting the baseline.

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

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

The description clearly states it retrieves live stock by date and ticket type using a specific API endpoint. It distinguishes itself from sibling tools like public_events_get (event details) and public_orders_create (order creation).

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 'Consultar antes de armar una orden' (check before building an order), indicating when to use it. No exclusions or alternative statements are provided, but the context is clear.

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

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

No annotations are provided, so the description carries full responsibility. It indicates the HTTP method (GET) and that the operation is public, implying it is read-only and safe. However, it does not explicitly state that it is non-destructive, idempotent, or describe any response structure or edge 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, concise sentence that immediately conveys the tool's purpose. It is front-loaded with the action and resource, with no redundant information, making it efficient for an AI agent to parse.

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

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

Given the tool's simplicity (one parameter, no output schema), the description is adequate but not complete. It lacks information about the returned fields (e.g., event title, date, location) and any constraints (e.g., authentication, data freshness). For a public details endpoint, more context would improve 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?

The input schema already provides a description for the single parameter 'slug' ('Slug del evento'). The tool description adds no additional semantic meaning beyond what the schema offers, so the baseline score of 3 is appropriate.

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

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

The description clearly states it retrieves public event details by slug, using a specific verb ('Detalle') and resource ('evento por slug'). It distinguishes itself from sibling tools like 'public_events_list' (listing) and 'public_events_availability' (availability), leaving no ambiguity.

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

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

The description does not explicitly specify when to use this tool versus alternatives like 'public_events_list' or 'public_events_availability'. Usage is implied (when you have a slug and need event details), but there is no direct comparison or exclusion criteria.

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 the burden of behavioral disclosure. It states the tool is public and requires no login, which is helpful. However, it doesn't confirm read-only nature, pagination details, or other side effects. The description is minimally adequate but not thorough.

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

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

Single sentence front-loads the purpose (public catalog, no login). No wasted words. Efficient and immediately scannable.

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 7 optional parameters and no output schema, the description provides minimal context. It doesn't describe return format, pagination behavior, or how results are ordered by default. While the schema covers parameters, the tool's overall behavior is underdescribed.

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 high (86%), so the description adds little beyond the schema's parameter descriptions. The tool description does not explain the filtering or sorting semantics in more detail. With high schema coverage, a 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?

Description clearly states it's a public catalog of published events (B2C discovery without login). The tool name and description effectively communicate its listing purpose and distinguish it from sibling tools like public_events_get (single event) and public_events_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?

No explicit guidance on when to use this tool versus siblings like public_events_get or public_events_availability. The context implies it's for browsing/discovery, but lacks direct differentiation or usage constraints.

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

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

Description adds significant behavioral context beyond annotations: it creates an order (not idempotent), returns payment link, and explicitly states the agent does not process payment. No contradictions with annotations (idempotentHint=false, destructiveHint=false match creation semantics).

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 clear structure: first states action and output, second adds constraints and usage hints. 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?

Covers purpose, return value, constraints (general admission, same organizer), and a prerequisite action (check stock). Lacks error handling details but sufficient for a creation 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 description coverage is 75% (3 of 4 params described). The description does not add extra meaning beyond the schema; e.g., buyerEmail receives QR is already in schema description. Baseline score of 3 is appropriate as schema does most of the work.

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 creates a B2C order and returns a Mercado Pago payment link. It specifies the scope (general admission, same organizer) and distinguishes from sibling tools like public_events_availability and public_orders_get.

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

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

Explicitly tells the agent not to process payment, only deliver the checkoutUrl. Also recommends checking stock with public_events_availability beforehand. Could be improved by explicitly stating when not to use (e.g., for numbered or members-only events).

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 indicates the tool returns status and tickets, which suggests a read operation, but does not explicitly state that it is read-only, non-destructive, or describe any side effects. More transparency is needed.

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 key details. No extraneous information, front-loaded with the core functionality.

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

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

Given one required parameter, good schema coverage, and no output schema, the description provides sufficient context about what the tool does and returns. It could be enhanced by explicitly stating that it is a read operation, but overall it is adequate.

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

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

Schema coverage is 100% with a clear description of the 'id' parameter. The description adds context about what the id refers to (returned by public_orders_create) and what the tool returns (status and tickets), providing 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 the tool returns order status (pending, paid, expired, cancelled) and associated tickets when paying. It uses a specific verb and resource (GET /public/orders/{id}), and implicitly distinguishes from siblings like public_orders_create.

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 used after creating an order (id returned by public_orders_create), but it does not explicitly state when to use it, when not to, or mention alternatives. It lacks explicit usage guidance.

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

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool is rate-limited and that the email always goes to the original purchase email, which are important behavioral traits. However, it does not mention side effects (e.g., whether the previous email is invalidated) or return behavior.

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

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

The description is a single sentence with a parenthetical, containing only essential information. It is front-loaded and free of redundancy.

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

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

The tool is simple (2 parameters, no output schema), and the description covers the main action and constraints. However, it lacks information about return values or error conditions, which would be helpful 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 the baseline is 3. The description reiterates that the email must match the original purchase email, which is already stated in the schema. It adds no new semantics beyond the schema, so a 3 is appropriate.

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

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

The description clearly states the action: resending the QR/email of a ticket to the buyer's email. It includes the HTTP method and path, and the resource ('ticket') and verb ('resend') are specific. The sibling tools are unrelated to ticket resending, so no confusion.

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

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

The description mentions rate-limiting but provides no guidance on when to use this tool versus alternatives, nor when not to use it. No comparison to sibling tools or other methods is given.

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