Voice School Lesson Booking

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

With no annotations provided, the description carries the full burden of disclosing behavior. It explains the creation of a lead, the requirement of at least one contact method, and explicitly limits its scope by stating it cannot confirm lessons or create schedule items. This is meaningful context that goes beyond the basic schema.

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

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

The description is two concise sentences, front-loaded with the primary purpose. The second sentence adds a requirement and an exclusion, both earning their place without redundancy 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?

Given the 13 parameters and an output schema, the description provides essential context about the tool's purpose and constraints. It does not explain return values (covered by output schema) or every parameter, but it offers enough for an agent to understand the action and its limitations. Sibling tool differentiation could be stronger, but the description is self-sufficient for most 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 description coverage is 0%, so the description must compensate. It adds the key constraint that 'requires name and at least one contact method,' which clarifies the relationship between the name and contact fields. However, it does not describe the other 12 parameters, relying on the schema's titles and defaults, so it only partially compensates.

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: 'Create a request-first lead for an online vocal lesson.' It distinguishes this from siblings by explicitly noting it never confirms a lesson or creates a schedule item, which sets it apart from tools like search_lesson_availability or list_lesson_options.

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 for when to use this tool: when you need to initiate a request-first lead. It also includes an explicit exclusion ('never confirms a lesson or creates a private schedule item'), which helps avoid misuse. However, it does not directly name alternative tools or provide explicit when-not-to-use guidance beyond this exclusion.

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 does not state that the tool is read-only or describe side effects, but the verb 'List' implies a safe read operation. Details like 'active' and 'live database' add some behavioral context, but return format and any caveats are not disclosed.

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 that efficiently communicates the tool's purpose without unnecessary words. It earns its place and is easy 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?

The tool is simple with 2 optional parameters and an output schema that describes return values. The description is adequate for a listing tool but leaves parameter semantics unexplained. Given the output schema, return values need not be described, but parameter guidance would make the description more 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 schema has 2 parameters (language, coach_slug) with 0% description coverage. The description mentions 'for a coach' which hints at coach_slug, but does not explain language or how these parameters affect the results. The description fails to compensate for the lack of 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 action ('List'), the resource ('active lesson services and prices for a coach'), and the context ('from the live Voice School database'). This is distinct from sibling tools like create_lesson_request (write) and search_lesson_availability (search availability).

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

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

The description implies the tool is for viewing a coach's offerings, which is clearly different from creating a request or searching availability. However, it does not explicitly state 'use this when...' or mention alternatives, so it lacks explicit exclusions.

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

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

With no annotations, the description carries the transparency burden. It discloses a key privacy trait ('never includes private learner data') and the calculation basis ('working windows and busy intervals'), but omits authentication, rate-limiting, or failure behaviors.

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 the primary purpose stated first and a secondary privacy note second. Every sentence adds value and there is 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 an output schema present, return values are covered, but the tool's core operation and parameter interplay remain underspecified. The description is adequate for a high-level gist but lacks enough context for an agent to confidently invoke it with correct parameters, especially with sibling tools present.

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%, yet the description offers no explanation of any parameters, such as coach_slug, date_from/to, or user_timezone. It does not compensate for the missing schema descriptions, leaving parameter semantics entirely to the schema's structural details.

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: finding free requestable lesson times using coach working windows and busy intervals. It goes beyond a tautology but does not explicitly differentiate from sibling 'list_lesson_options', which may offer similar capabilities.

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 searching availability but does not provide explicit when-to-use guidance, alternatives, or exclusions. No information distinguishes this from 'list_lesson_options' or indicates when to prefer it.

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 burden of behavioral disclosure. It indicates the tool returns informational content but does not clarify whether the operation is read-only, how the language parameter affects output, or what the response contains beyond 'links'. This is minimal behavioral context.

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 states the tool's purpose. There is no redundancy or unnecessary detail, and it is front-loaded with the key terms 'public description', 'policy', and 'catalog links'.

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 this is a simple info tool with one optional parameter and an output schema (which can explain return values), the description is minimally adequate. However, it omits the role of the 'language' parameter and provides no examples of the links, leaving some ambiguity for an agent deciding between this and sibling tools.

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 one optional 'language' parameter with 0% description coverage. The description does not mention this parameter at all, providing no additional meaning beyond the schema. It fails to explain what language affects (likely the language of the returned policy/catalog links) or any constraints.

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 what the tool does: it provides public description, policy, and catalog links for Voice School online vocal lesson requests. This is distinct from the sibling tools (create, list, search), though it lacks an explicit verb like 'returns' or 'provides'.

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

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

Usage is implied: this tool should be used when general information about Voice School is needed, as opposed to creating requests, listing options, or searching availability. However, there is no explicit guidance on when to use it versus alternatives, nor any mention of when not to use it.

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