aisha

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It reveals that cancellation is 'una acción definitiva' (a definitive action), requires confirmation with the person, has an instant effect on the time slot, and requires folio and name to match. This is valuable context, though it does not mention error cases or permissions.

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 succinct and well-structured: it opens with the action and effect, then lists requirements, and ends with a warning and follow-up instruction. Every sentence earns its place, and there is no redundant repetition of schema 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 2-parameter tool with an output schema, the description covers the core purpose, required credentials, irreversibility, and a related workflow. It does not elaborate on error handling, but that is likely covered by the output schema. The description is complete for the tool's 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?

The schema provides only parameter names without descriptions, leaving 0% coverage. The description adds that the name must be the one used when making the reservation and that both folio and name must match, giving some meaning. However, it does not explain the format of folio or how to obtain it, so ambiguity remains.

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

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

The description clearly states the tool's function with the verb 'Cancela' (cancels) and a specific resource: 'una reserva existente en Aisha y libera la hora al instante.' This distinguishes it from sibling tools like crear_reserva (create) and consultar_reserva (query).

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

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

The description explicitly says when to use this tool (to cancel an existing reservation) and provides an alternative workflow for changing times: 'primero cancela con esta herramienta y luego crea la nueva con crear_reserva.' This names the sibling tool and gives clear sequencing.

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

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

With no annotations, the description carries the full burden and does disclose conditional behavior: with persona it returns only that person's hours, without it returns hours when someone is free. It does not mention authentication, rate limits, or error cases, but the read-only nature is strongly implied by 'consulta' and 'devuelve'.

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

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

Three concise sentences front-load the core purpose and date format, then add only the conditional behavior needed to use the persona parameter correctly. No filler or repetition.

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 3-parameter availability query with an output schema, the description covers all essential call semantics: required business/date, optional person, date format, and expected output behavior. It lacks only explicit handling of invalid businesses or dates and any reference to sibling lookups like listar_negocios, but these are not critical.

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 descriptions are absent, but the description compensates well: it specifies the date format (AAAA-MM-DD), explains the optional persona parameter with a concrete scenario and fallback behavior, and makes negocio's role clear. This goes well beyond the bare 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 names a specific action ('Consulta los horarios libres'), a resource (negocio), and a date, plus an optional filter by person. This clearly distinguishes it from sibling reservation-management tools like consultar_reserva and crear_reserva.

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?

It gives clear context for when to call the tool (when free slots are needed) and detailed conditional guidance for the persona parameter. It does not explicitly name sibling alternatives or state when not to use it, but the context is unambiguous.

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 reveals the critical behavior that both folio and nombre_cliente must match, framed as protection against querying others' reservations. It does not describe error details or return format, but the security constraint is a significant behavioral trait.

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

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

The description is two sentences, front-loaded with the main purpose, then prerequisites, then usage context. Every sentence earns its place; no filler or 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 query tool with only two parameters, the description covers purpose, prerequisites, and use cases. An output schema exists, so not describing return values is acceptable. It lacks details on failure scenarios, but the provided context is sufficient for an agent to select and invoke correctly.

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

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

The input schema provides only parameter names and titles with zero descriptions. The description compensates by giving a concrete folio example ('FILOSALO-0003') and clarifying that nombre_cliente is the name under which the reservation was made, adding meaning beyond the bare schema.

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

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

The description clearly states the tool's purpose: to check the status of an existing reservation in Aisha. It uses a specific verb ('consulta') and resource ('reserva existente'), and distinguishes it from siblings like cancelar_reserva or crear_reserva by focusing on status inquiry.

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?

It explicitly provides use cases: 'Úsala cuando la persona pregunte "¿sigue en pie mi cita?" o quiera confirmar fecha, hora o dirección.' This gives clear when-to-use guidance, but does not explicitly mention when not to use it or name alternative tools, which is a minor gap.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly warns not to invent contact data, explains why the business needs it, and instructs the agent to offer a telephone fallback if the user declines. It also covers optional persona behavior and describes the return payload (folio, assigned person, address, map link, arrival lead time). While it does not discuss failure modes or side effects beyond creation, the provided behavioral guidance is substantial and valuable.

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

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

The description is longer than average but well structured with a clear summary, a required-fields list, and separately labeled notes for contacto_cliente and persona. It front-loads the core purpose and then adds necessary behavioral nuance. Some repetition occurs around the contact requirement, but each section serves a distinct purpose and the length is justified by the need to prevent data fabrication and misrouting.

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 tool with 7 parameters, no schema descriptions, and no annotations, this description is highly complete. It covers required and optional inputs, format expectations, sensitive data-handling rules, and return values. The output schema may exist, but the description still usefully summarizes what the tool returns. An agent has enough context to invoke this tool correctly in a booking conversation.

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 0%, so the description must compensate, and it does thoroughly. It clarifies negocio as id or name, gives format for fecha (AAAA-MM-DD), provides an example for hora, explains contacto_cliente as the attendee's phone or WhatsApp, and explains the optional persona parameter in detail. All seven parameters receive meaningful semantic guidance beyond their bare schema definitions.

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 opens with a clear, specific statement: 'Crea una reserva en un negocio.' It also names the object being created, lists required inputs, and distinguishes itself naturally from sibling tools like cancelar_reserva and consultar_reserva by focusing on the creation action. An agent can immediately identify this as the booking-creation tool.

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

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

The description explains when to call the tool by specifying required fields and even guides behavior around obtaining contacto_cliente and handling the optional persona field. It references ver_servicios for staff names, giving useful cross-tool context. It does not explicitly contrast with sibling tools or state when not to use the tool, but the usage 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?

With no annotations, the description carries the full burden. The verb 'Lista' implies a read-only operation, and it discloses the output fields (giro, ciudad, estado de verificación), adding useful behavioral context. It does not explicitly state 'does not modify data' or mention limitations, but the low complexity keeps this acceptable.

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

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

The description is a single, front-loaded sentence with no filler. It efficiently conveys the action, scope, and output fields, with every word contributing meaning.

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 zero-parameter, read-only listing tool with an output schema present, the description is complete. It states what is listed and key output attributes. No missing critical information given the tool's simplicity.

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

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

The tool has zero parameters, so the baseline is 4 per the rubric. The description adds no parameter info because there are none; the schema is empty. The description's mention of output fields adds contextual value beyond the schema.

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

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

The description uses a specific verb 'Lista' (lists) with a clear resource ('todos los negocios conectados a Aisha') and specifies included fields (giro, ciudad, estado de verificación). It clearly distinguishes from sibling tools, which focus on reservations and services, not business listing.

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

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

The description clearly indicates the tool's scope ('todos los negocios conectados a Aisha') and the context is clear given sibling tool names (cancellations, reservations, services). However, it does not explicitly name alternatives or provide exclusions, so it stops short of a 5.

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

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

With no annotations, the description carries the full burden and discloses a key behavioral trait: it only registers the request, not publish the business, and mentions the verification step with a person. It does not cover side effects beyond that, but the critical limitation is clearly highlighted.

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 efficiently structured: first sentence defines purpose, second gives usage context, third lists data requirements, and fourth highlights the important caveat. Every sentence adds value with no redundancy.

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

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

The tool has 9 parameters and no schema descriptions, yet the description covers what the tool does, when to use it, what data to collect, and the critical consequence (no publication until verification). An output schema exists, so return values are not needed in the description. It is complete for its purpose.

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

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

Schema coverage is 0%, so the description compensates by listing all required data (nombre comercial, giro, ciudad, etc.) and provides example values for 'giro' (barbería, estética, salón, spa). It does not explicitly mention the optional 'notas' parameter, but covers most parameters with meaningful 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?

The description clearly states the tool registers a business request to appear in Aisha and be bookable, with a specific verb ('Registra la solicitud') and resource ('un negocio'). It distinguishes itself from sibling tools focused on reservations and browsing by targeting business owner sign-up.

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 'Úsala cuando el dueño de un negocio pida darse de alta' and specifies required data collection steps. It also clarifies an important exclusion: the tool does not publish the business, providing clear when-to-use and what-not-to-expect guidance.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation through 'Muestra' (shows) but does not explicitly state that it makes no changes or disclose any limitations (e.g., what happens if the business is not found). It also doesn't mention auth requirements or rate limits. The description states what data is shown, which adds some transparency, but it lacks explicit behavioral disclosure.

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

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

The description is two sentences, front-loaded with the main purpose and followed by the input note. Every word earns its place; there is no verbosity or 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?

For a tool with one required parameter and an output schema, the description fully covers what it does and how to invoke it. The output schema handles return value details, so the description's focus on purpose and input is complete. No critical context is missing.

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

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

Schema coverage is 0%, so the description must compensate. It does so by explaining that the 'negocio' parameter accepts an ID or part of the name, which is not evident from the schema alone. It also clarifies that the parameter identifies the business. However, it doesn't specify format or length, but given the simple single-parameter design, this is adequate.

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

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

The description clearly states the tool's function: 'Muestra los servicios, precios, horario, dirección y cómo llegar a un negocio' (shows services, prices, schedule, address, and how to get to a business). It specifies the resource (a business) and the exact data returned, distinguishing it from siblings like listar_negocios which lists businesses rather than showing details.

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: use this when you need detailed service information for a specific business. It does not explicitly mention alternatives or when not to use it, but the purpose is unambiguous. The input instruction 'Acepta el id o parte del nombre' gives practical usage guidance.

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