Voice School Lesson Booking

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

With no annotations, the description carries full burden. It discloses a key behavioral boundary (never confirms or schedules), which is valuable. However, it omits other potential side effects like notifications, permissions, or idempotency, but for a creation tool this is reasonably transparent.

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, front-loaded with the core action, and no fluff. Every sentence adds value: the first defines the action, the second clarifies constraints.

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?

Despite having an output schema, the description is incomplete for correct invocation. With 13 parameters and no annotations, it fails to explain the meaning or usage of most fields, particularly the slugs and scheduling-related params. The mention of contact method is partial and conflicting with the 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 coverage is 0%, so the description must compensate. It mentions 'name' and 'at least one contact method' but only implicitly, and does not explain most of the 13 parameters (coach_slug, service_slug, requested_start, etc.). Additionally, it contradicts the schema by requiring a contact method when the schema only requires name, which could mislead an agent.

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 creates a request-first lead for an online vocal lesson, using a specific verb ('Create') and resource. It distinguishes itself from sibling tools (list_lesson_options, search_lesson_availability, voice_school_info) by explicitly noting this does not confirm a lesson or create a schedule item, setting it apart from search/list/info tools.

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 to create a lead, not to confirm a lesson or schedule. It gives a negative constraint ('never confirms a lesson or creates a private schedule item') but does not explicitly name alternative sibling tools, so it falls slightly short of full when-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 provided, the description carries the full burden of behavioral disclosure. It does add the useful auth requirement ('Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token') and reveals an upsert-like 'create or update' behavior, but it never explains what identifies an existing post for update, whether the update overwrites all fields, or what the publish boolean does (e.g., whether publish=true bypasses draft state). For a mutating tool, these are significant undisclosed 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 a single front-loaded sentence that states the action first and the credential requirement second, with no wasted words. It earns its place by naming the core payload fields and the auth token, though the same sentence could have carried more decision-useful content (e.g., draft-vs-publish semantics) without becoming bloated.

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 complexity — 21 parameters, 6 required, a mutating operation, no annotations, and 0% schema coverage — a one-sentence description is inadequate. The output schema covers return values, but critical context is missing: update matching semantics, publish behavior, the meaning of the required channel_* fields, and the relationship to publish_social_post. An agent would likely need to inspect sibling tools or attempt trial calls to understand the full contract.

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 names only a subset of the 21 parameters (seo_title, meta_description as 'description', keywords, tags, source_post_url, blocks). This covers roughly a quarter of the parameters, leaving write_token's format, coach_slug, channel_slug/title/url, source_platform, language_code, external_post_id, raw_text, body, and source_published_at unexplained by both the schema and description. The partial enumeration helps but does not come close to compensating for zero schema coverage.

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 ('Create or update') with a clear resource ('a trainer social post') and enumerates the content payload (SEO title, description, keywords, tags, source URL, blocks). It is clearly more specific than the tool name alone, but it doesn't explicitly say 'draft' even though the tool is named create_social_post_draft, and it doesn't explicitly distinguish itself from the sibling publish_social_post — an agent could confuse 'create or update a social post' with publishing.

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 offers no guidance on when to use this tool versus its siblings (publish_social_post, list_social_posts, upsert_social_channel). The only context provided is the token requirement, which is a prerequisite rather than a usage signal. There are no exclusions, no alternative routing, and no indication of whether this tool is the right choice for drafting, editing, or both.

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?

No annotations are provided, so the description must carry the full burden. It mentions 'published' posts and dual URL fields, but does not disclose filtering behavior, default scope, ordering, pagination, or any side effects (though likely a read-only list). The presence of an output schema helps somewhat, but significant behavioral context is missing.

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 front-loads the core purpose and key return data. It earns a high score for brevity and clarity, though it does not include any additional context or usage hints that could be fit into the same space.

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 a simple list operation with an output schema present, which reduces the need to document return values. However, with zero annotations, zero parameter documentation, and no usage guidance against siblings, the description is only marginally adequate for an agent to invoke it correctly with proper filter 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 parameters (limit, language, platform, coach_slug, channel_slug) are entirely undocumented in both the schema and the description. The description adds no meaning about what these filters control or how they relate to trainer channels. With 5 undocumented parameters, the description fails to compensate.

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 ('list') and resource ('published trainer social posts') and clarifies that it returns both canonical and original source URLs. However, it does not explicitly differentiate from siblings like 'list_lesson_options' or 'publish_social_post', though the resource is clear 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?

There is no guidance on when to use this tool versus other social-post-related siblings such as 'create_social_post_draft', 'publish_social_post', or 'upsert_social_channel'. The context signals show optional filters, but no conditions are described for choosing this tool over alternatives.

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 behavioral disclosure. It does disclose the required write token and the validation step, which are useful. However, it does not mention that publishing is a public, likely irreversible side effect, nor what happens if source URL validation fails.

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 short, focused sentences with no redundant information. The main action is front-loaded and the auth requirement is stated directly. Every word 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 two-parameter tool with an output schema, the description is close to adequate, but it fails to define slug and does not clarify the public side-effect nature of publishing. It gives enough to select the tool but not quite enough to invoke it with full confidence.

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 explains that write_token should be SOCIAL_POSTS_MCP_WRITE_TOKEN, which adds value, but the required slug parameter is left completely undefined, leaving a critical meaning 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 uses a specific verb, 'publish', and a specific resource, 'prepared trainer social post', and adds a distinguishing precondition: 'after source URL validation'. This clearly separates it from sibling tools like create_social_post_draft and list_social_posts without 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 phrase 'prepared trainer social post' implies this tool is for posts already created and ready to publish, not for drafting or listing. It establishes context for when to use it, though it does not explicitly name alternatives or state 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.

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 discloses how the tool works ('using coach working windows and busy intervals') and adds a privacy guarantee ('The response never includes private learner data'). This goes beyond the basic 'search' concept and provides useful behavioral context, though it does not mention rate limits, pagination, or read-only status explicitly. For a read-only search tool, this is reasonably transparent.

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, both front-loaded with essential information. The first sentence delivers the primary purpose, and the second provides a key privacy note. No redundant filler or fluff; every word 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?

The tool has six optional parameters and an output schema, so the description needs to explain how parameters relate to the search behavior. It does not explain the purpose of date_from/date_to, limit, or user_timezone. While the output schema covers return values, the lack of parameter guidance and absence of annotations leaves gaps for an agent trying to customize a search. The high-level purpose is clear, but the description is not fully complete for effective invocation in varied scenarios.

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% — no parameter descriptions exist. The description does not mention any of the six parameters (limit, date_to, date_from, coach_slug, service_slug, user_timezone). It only vaguely refers to 'coach working windows and busy intervals,' which hints at coach/service relevance but provides no concrete meaning for the parameters. The tool name and schema titles carry some meaning, but the description adds negligible value for parameter understanding.

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: 'Find free requestable lesson times using coach working windows and busy intervals.' It uses a specific verb ('Find') and resource ('free requestable lesson times'), and the method distinguishes it from sibling tools like create_lesson_request (which creates) and list_lesson_options (which lists options). It is unambiguous and immediately understood.

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's usage context (searching for available slots) but does not explicitly state when to use it over alternatives. It does not reference sibling tools or provide exclusion criteria, such as 'Use this to check real-time availability, as opposed to list_lesson_options which gives fixed offerings.' Thus, the usage guidance is only implicit, not explicit.

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 disclosure burden. It usefully reveals that a special write token is required and implies upsert semantics, but it does not explain what happens on update, whether existing records can be deactivated, or what side effects the write may have.

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 short, front-loaded, and contains no fluff; both sentences earn their place. It is slightly under-sized for a tool with nine parameters, but it is efficiently written.

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 omits essential context for most required parameters and never explains platform/channel_type semantics or the relationship between slug and existing records. The write_token mention is the only substantive operational detail in an otherwise thin definition.

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 explain parameters, but it only enriches write_token. No meaning is added for coach_slug, platform, title, slug, url, is_active, description, or channel_type, leaving agents to guess their formats and allowed values.

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 verb ('Add or update') and resource ('social channel/group that trainer posts are attached to'), making the core action clear. It does not explicitly differentiate from the sibling tool 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 is given about when to use this tool versus alternatives such as upsert_trainer_social_link or create_social_post_draft. The write_token requirement is a prerequisite, not a selection criterion, so an agent receives no help choosing among siblings.

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 mutating upsert operation and names the required auth credential: 'Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token.' With no annotations provided, the description carries the behavioral burden, and this is only partial: it does not explain whether existing links are overwritten, how is_active/display_order are treated, or what happens on conflict. The token requirement adds meaningful context beyond the 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 compact and front-loaded: one sentence for the action and one for the auth requirement. There is no filler or redundancy, though the phrase 'public round social icon link' is slightly awkward and could be clearer.

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 operation with no annotations, the description is too sparse. The auth token detail is helpful, but there is no mention of what fields like platform, url, or label should contain, no usage context beyond the action itself, and no guidance on upsert conflict behavior. The presence of an output schema reduces the need to document return values, but the input-side gaps remain significant.

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 8 parameters. It only clarifies write_token by naming the required secret. Parameters like label, handle, display_order, and is_active receive no semantic explanation, leaving the agent to infer their meaning from titles and defaults alone.

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 and resource: 'Add or update a public round social icon link for a Voice School trainer.' This clearly identifies the tool's action and target, and it is distinguishable from siblings like create_social_post_draft and upsert_social_channel by the focus on trainer social icon links. However, it does not explicitly differentiate itself from upsert_social_channel.

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 provided about when to use this tool versus alternatives. It does not mention that upsert_social_channel is for channels, that create_social_post_draft is for drafts, or any conditions that would make this tool the preferred choice. The auth token requirement is useful but does not constitute 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 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.