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

With no annotations, the description carries the disclosure burden, and it clearly states the observable behavior: returning a URL rather than article content or a search result list. It does not discuss failure behavior or authentication, but for a simple read-only lookup that is a minor gap.

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 that leads with the action and object, with no filler or repetition. Every word contributes to telling the agent what the tool does and when it applies.

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 tool with no output schema, the description is nearly complete: it specifies the input type, the return value, and the domain. The only missing context is explicit guidance about which sibling tools cover other question types, but that is more of a usage-guideline nicety than a correctness gap.

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 100%, so the baseline is 3; the schema already explains that 'query' is the Kalyvox setup or product question. The description's addition of 'configuration' broadens the term slightly but provides no examples or syntax guidance.

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 verb ('Return'), a concrete resource ('official Kalyvox help-center URL'), and a clear scope ('setup, configuration or product question'). This makes it easy to distinguish from sibling tools like get_kalyvox_overview or get_kalyvox_features without opening their schemas.

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 says the tool is for setup, configuration, or product questions, which gives useful context for when to use it. However, it never names alternatives or states when not to use it, leaving the choice among the get_kalyvox_* siblings implicit rather than 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 full burden. It does state the action ('list') and the general subject, which is minimally adequate. However, it does not disclose the return format, level of detail, or any limitations (e.g., whether it omits detailed specifications).

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, direct sentence with no filler. The key information ('List', 'main capabilities', 'Kalyvox') is front-loaded, and 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 zero-parameter tool with no output schema, the description is mostly sufficient. However, given the sibling tools, some context about how 'features' differs from 'overview' would improve completeness. As is, it is adequate but leaves minor ambiguity.

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?

There are no parameters, so the description is not required to add parameter-level meaning. The baseline of 4 applies because the schema has no properties and the description correctly focuses on the operation itself.

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 ('main capabilities of the Kalyvox AI phone receptionist'). It is clear about what the tool returns, though it does not explicitly distinguish itself from get_kalyvox_overview, which could overlap in scope.

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 on when to use this tool versus its siblings such as get_kalyvox_overview or get_kalyvox_integrations. The agent must infer the appropriate context from the tool name alone, with no exclusions or alternatives mentioned.

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. The verb 'List' implies a read-only operation that returns a set of items, which is transparent for a simple zero-parameter tool. However, the qualifier 'main' is vague and does not explain filtering criteria or whether the result is exhaustive, leaving some ambiguity about the tool's exact 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?

The description is a single, front-loaded sentence with no filler or repetition. It efficiently conveys the tool's core purpose without waste.

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 list tool with no output schema, the description adequately states what is returned (main integrations). It is complete enough for basic invocation, though the vague 'main' qualifier and absence of any sibling differentiation slightly reduce completeness.

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 and the schema coverage is 100%, so the schema already fully describes the parameter surface. Per the baseline for zero-parameter schemas, a score of 4 is appropriate; the description does not need to add parameter 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 resource ('main integrations available with Kalyvox'), clearly identifying what the tool does. It also distinguishes itself from siblings like get_kalyvox_features and get_kalyvox_links by naming a distinct resource type.

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 no guidance on when to use this tool versus alternatives. There is no mention of a preferred context, exclusions, or a pointer to a sibling, despite several closely related tools existing. The agent is left to infer usage solely from the name and description.

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 implies a read-only lookup and specifies the output type, but it adds no context about link freshness, format, or coverage limits. For a zero-parameter informational tool, this is minimally adequate.

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 with no filler. Every word contributes to describing the action and output.

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 no-parameter tool, the description covers all three link categories and marks them as official. It is complete enough to invoke successfully, though adding a short sibling-routing note would improve 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?

There are no parameters, so schema coverage is trivially complete. The rubric assigns a baseline 4 for zero-parameter tools, and the description does not need to add parameter 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?

States a clear verb and resource: returns official product, integration, and help-center links for Kalyvox. It broadly separates from overview/features, but overlaps with get_kalyvox_integrations and find_kalyvox_help, so it does not fully differentiate among all 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?

No guidance on when to use this tool versus alternatives. It neither names when this tool is preferred nor explains how it differs from get_kalyvox_integrations or find_kalyvox_help.

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 of behavioral disclosure. It discloses that the output is a concise overview rather than detailed data, but does not mention whether it is purely read-only, what content it includes, or the response format. For a simple get tool this is thin but not misleading.

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-formed sentence that states the purpose directly with no filler. It is appropriately sized and 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 description is adequate for a zero-parameter overview tool, but it leaves out details about the response content and does not help an agent distinguish this from the overlapping sibling get_kalyvox_features. With no output schema and no annotations, slightly more context would make it fully 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 tool has zero parameters, so there is no parameter documentation needed. The description adds useful context about what the response will cover, which satisfies the baseline for parameter-free tools.

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 tool as retrieving a concise overview of Kalyvox and its AI receptionist function. It names a specific resource, though it does not explicitly differentiate itself from get_kalyvox_features, which could partially overlap.

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 about when to use this tool versus its siblings. It does not explain that get_kalyvox_features, get_kalyvox_integrations, or get_kalyvox_links are more specific alternatives, nor does it state any conditions for choosing the overview.

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