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 present, so the description carries the full disclosure burden. It usefully discloses the token requirement and the dual create/update semantics, but it does not mention that the publish parameter can take a draft live, nor how an update overwrites existing content — both consequential behaviors for a mutation 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, each earning its place: the first summarizes purpose and content shape, and the second states the authentication requirement. It is dense but not bloated, and the purpose is 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?

For a 21-parameter creation tool with zero annotations and zero schema descriptions, this description is incomplete. The update-vs-create trigger, the redundancy of channel_title/channel_url alongside channel_slug, and the publish flag's side effects are all left to inference. The output schema mitigates only return-value questions, not invocation semantics.

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, but it names only the headline content fields (SEO title, keywords, tags, source URL, text/video blocks). The six required parameters (coach_slug, channel_slug, channel_title, channel_url, source_post_url, write_token) and the remaining optional fields such as slug, excerpt, language_code, and source_platform are left unexplained in both schema and 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 states a clear verb+resource ('Create or update a trainer social post') and enumerates the content payload (SEO title, description, keywords, tags, source URL, ordered text/video blocks). The name 'draft' plus the sibling publish_social_post imply a drafting stage, but the description does not explicitly differentiate itself from 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 gives no guidance on when to use this tool versus siblings such as publish_social_post, upsert_social_channel, or list_social_posts. The only prerequisite mentioned is the write token, so an agent gets no selection cues and no 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?

No annotations are provided, so the description carries the full burden. It adds useful behavioral context by stating 'active' (filtering only active services) and 'live' (real-time database source). However, it does not disclose the read-only nature, potential side effects, or any limitations such as pagination or required permissions, which would be expected given the absence of annotations.

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 front-loads the main action and resource. Every word adds value, and there is no redundant or filler content. It is appropriately sized for the tool's simplicity.

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 and has an output schema, so the description does not need to explain return values. It clearly states the purpose, target coach, and data source, making it mostly complete. However, the lack of parameter explanation and explicit usage guidance relative to siblings slightly reduces completeness, though the output schema compensates for return-value details.

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 with 0% description coverage, and the description does not compensate. It mentions 'for a coach' which loosely maps to coach_slug, but it completely ignores the language parameter. There is no explanation of parameter formats, defaults, or how they affect the output, leaving the agent with insufficient information.

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 ('List') and identifies the resource ('active lesson services and prices for a coach') plus the source ('live Voice School database'). This clearly distinguishes it from sibling tools like create_lesson_request (creation), search_lesson_availability (availability search), and voice_school_info (general school 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 provides clear context for when to use this tool: to retrieve active lesson services and prices for a specific coach. It does not explicitly mention alternatives or exclusions, but the sibling tool names make the distinctions obvious, so the context is sufficient without overt when-not-to-use 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 transparency burden. It communicates a read-only list of published posts and the URL fields returned, but it does not disclose pagination, ordering, scope (e.g., current trainer vs any trainer), or any auth/permission requirements.

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 sentence with no filler; the key verb, resource, status filter, and return detail are all 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?

The output schema exists, so return-shape concerns are reduced, and the description covers the main purpose. However, it is incomplete for a five-parameter tool: an agent cannot tell from the description which optional filters are available or how they behave.

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 for the five undocumented parameters. It does not explain limit, language, platform, coach_slug, or channel_slug, nor their defaults or filtering behavior.

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 ('List') and resource ('published trainer social posts') and adds output detail (canonical and original source URLs). This clearly distinguishes it from sibling tools like create_social_post_draft, publish_social_post, 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 intended use is implied: retrieve published trainer social posts. The word 'published' hints at when it applies, but the description gives no explicit guidance about when to choose this over alternatives or when not to use it, such as when drafts should go to create_social_post_draft.

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 available, the description carries the disclosure burden and covers meaningful behavioral ground: it requires an auth token and performs source URL validation before publishing. It does not detail side effects such as visibility or irreversibility, but the disclosed auth and sequencing exceed 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?

Two sentences, no wasted words, and the key action plus required condition are front-loaded. Every sentence adds 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 is close to sufficient, but the undefined slug and lack of failure behavior/error cases make it only minimally viable for a correct call.

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 explain the parameters. It correctly maps write_token to SOCIAL_POSTS_MCP_WRITE_TOKEN, but leaves slug undefined; the agent has to guess what value identifies the prepared post. This is a clear gap.

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 action ('Publish') on a specific resource ('prepared trainer social post') and adds a validation step. The word 'prepared' clearly separates it from sibling create_social_post_draft.

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 clear context: use this to publish a post that has already been prepared and after source URL validation. It does not explicitly name alternatives or state when not to use the tool, but the context is sufficient to route an agent correctly.

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?

The description discloses that this is a write operation requiring SOCIAL_POSTS_MCP_WRITE_TOKEN, an important auth prerequisite not covered by annotations (none are provided). However, it does not explain conflict behavior, partial-update semantics, or consequences of changing slug/url, leaving some behavioral burden unmet.

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 front-loaded sentence that names the operation and resource before the auth requirement, with no filler. Every phrase adds signal, and it is appropriately sized.

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 schema has no property descriptions and there are no annotations, the description covers only the core action plus one auth parameter. It omits sibling differentiation, required-field rationale, key/conflict semantics, and parameter details, so it is not complete enough for reliable invocation despite the output schema reducing the need to document return values.

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%, and the description only explains write_token. The meanings and relationships of coach_slug, platform, title, slug, url, is_active, description, and channel_type are left to inference from parameter names, which is insufficient for a nine-parameter upsert.

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 a specific action ('Add or update') and resource ('social channel/group') and ties it to trainer posts, so an agent knows what entity is being managed. However, it does not explicitly differentiate from the similarly named sibling upsert_trainer_social_link, so it stops short of a 5.

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 versus alternatives; it does not contrast with upsert_trainer_social_link or other sibling tools. The only usage hint is the required write_token, which is a prerequisite rather than a selection rule.

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, but it only reveals that the operation is an upsert and requires a specific token. It does not disclose what happens to an existing link, whether the operation is idempotent, or any side effects beyond add/update.

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 with the action and resource front-loaded. The odd 'public round' wording is slightly confusing, but otherwise there is 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 an 8-parameter write tool with no annotations and no parameter descriptions, this definition is incomplete. It omits what 'public round' means, what platform values are valid, and how display_order or is_active affect behavior, leaving an agent to guess from names.

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 should compensate, but it only explains write_token. The other seven parameters (coach_slug, platform, url, label, handle, is_active, display_order) are left entirely to their names and schema defaults.

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 action ('Add or update') and a specific resource ('public round social icon link for a Voice School trainer'), which clearly distinguishes it from post-publishing and channel-management siblings. The phrase 'public round' is somewhat ambiguous, but the overall purpose is still evident.

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 is given about when to use this tool versus alternatives like upsert_social_channel or create_social_post_draft. The intended use is only implied through the resource name, with no explicit conditions or 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 burden of disclosing behavior. 'Public description, policy, and catalog links' suggests an informational, read-only operation, but it never explicitly states that no data is modified or how the language parameter affects the 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?

The description is a single concise sentence with no filler and the core subject is front-loaded. However, it is a noun phrase rather than a full behavioral statement, which slightly reduces clarity.

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?

Although an output schema exists, the description lacks usage context and fails to explain when to call this tool relative to siblings. It also omits the language parameter's role, leaving the description incomplete for effective tool selection and 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?

The only parameter, language, is not mentioned in the description. The schema provides only the property name and default 'en', with 0% description coverage, so the description does not compensate by clarifying supported values or effect on results.

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 identifies the resource (Voice School online vocal lesson requests) and states that the tool provides public description, policy, and catalog links. This distinguishes it from sibling tools (create, list, search), though it lacks an explicit verb like 'get' or 'retrieve'.

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 is given on when to use this tool versus alternatives. The description does not mention that it should be called before creating or searching for lesson requests, nor does it reference the sibling tools.

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