Yoya Booking

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 invalid slots will be rejected, that email receives the confirmation and calendar invite, that requiredFields must be answered, and that the response includes a cancellation/rescheduling link. This goes well beyond a bare action statement.

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 compact, information-dense, and front-loaded with the core action. Each sentence addresses a distinct operational detail with no filler 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 9 parameters and no output schema or annotations, it covers the critical calling requirements and return behavior. It could additionally clarify slug/name, but those are reasonably inferable from the schema and context.

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

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

Schema coverage is 56%, so the description adds meaningful context for undocumented parameters: slotId must come from list_available_times and email is the delivery target. It also clarifies the conditional semantics of meetingType and how fieldAnswers should be keyed.

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

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

The description clearly identifies the action: booking a meeting on a host's page. The verb 'Book' plus the resource 'a host's page' distinguishes this from the sibling tools that list or retrieve bookings/times.

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 provides concrete preconditions and conditional usage: use a slot id from list_available_times, pass meetingType when multiple options exist, and fill fieldAnswers for requiredFields. It does not explicitly contrast with get_booking, but the operational guidance is clear enough.

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

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

With no annotations, the description must carry the behavior disclosure; 'Look up' conveys a read-only operation and the manage-token context hints at authorization. It stops short of stating side-effect-free behavior, error/not-found cases, or any rate limits, so it provides moderate 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?

A single 24-word sentence, front-loaded with the action and resource, with the token-source clarification parenthetically. Every clause earns its place; no redundant wording.

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 one-parameter lookup with no output schema, the description covers the essential invocation details—what identifies the booking and what fields the caller can expect. It could be more complete with an explicit note about when a manage token is available or when to use get_booking_page instead, but overall it is not missing critical inputs.

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%, and the description compensates by explaining the token's real-world provenance: the code in a yoya.ai/b/<token> link. For a single-parameter tool this fully clarifies what to pass and where to find it, beyond the bare minLength constraint.

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 specific verb ('Look up'), names the resource ('a booking'), and identifies the exact input ('manage token'). It also states the purpose ('see its status and time'), which clearly separates it from the booking/availability/listing siblings.

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

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

The description implies a use case—use when you have a manage-token link and need booking status/time—but it never explicitly says when to prefer this tool over get_booking_page, book_meeting, or list_available_times, nor provides exclusions. This is implied usage, not clear routing 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 provided, the description carries the full burden. It discloses the null-on-no-active-page behavior, the 'public' and 'active' preconditions, and lists the returned fields. It doesn't state read-only status, but 'look up' reasonably implies it.

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, no filler. The action comes first, followed by input guidance, then the output summary. 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?

For a one-parameter tool with no output schema and no annotations, the description fully covers how to call it, what to pass, what it returns, and the null edge case. Nothing an agent needs to invoke it correctly 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?

The schema only defines 'slug' as a string with minLength 1. The description enriches this by defining a slug as 'the part after yoya.ai/' and stating that the whole link is also accepted — meaning the schema alone would not convey how to invoke the tool correctly.

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

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

The description clearly identifies the action ('look up') and the resource ('public Yoya booking page'), and enumerates the returned data. It does not explicitly differentiate from the sibling 'get_booking', but the consistent use of 'page' makes the object distinct enough.

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 provides practical input guidance ('Pass its slug... or the whole link — either works') and implies the tool is for retrieving public booking-page details. However, it never addresses when to prefer this over siblings like get_booking or book_meeting, and gives no exclusion conditions.

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 disclosure burden. It reveals that slot ids are opaque, time labels are human-readable and in the host's timezone, and only returned ids are bookable. This goes beyond basic list semantics, though it omits minor details like empty-result or error 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?

Three sentences with zero filler: the core action is front-loaded, followed by the return-value shape and a critical routing note. Every sentence earns its place.

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

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

For a one-parameter tool with no output schema and no annotations, this description covers the essential context: return value shape, timezone, and how the output is used by book_meeting. Missing edge cases (e.g., what happens when no slots exist) are non-critical for correct invocation.

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. It partially does by saying the page is identified by 'its slug or its full link', which adds meaning to the lone slug parameter. However, it doesn't specify the expected format of either, leaving ambiguity about whether the slug field accepts a full URL.

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 states a specific verb and resource: 'Return the open time slots for a booking page'. It clearly distinguishes itself from siblings by explicitly linking the output to book_meeting ('Pass a slot id to book_meeting'), which prevents confusion with get_booking and get_booking_page.

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

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

Usage is explicitly routed: the description tells the agent to pass a returned slot id to book_meeting and warns never to invent a time. This is an unambiguous when-to-use that also names the sibling consuming the output, leaving no inference needed.

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