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

No annotations are provided, so the description carries the burden. It says 'Get the link', implying a read-only retrieval operation with no side effects. It also clarifies that the function returns a link rather than performing the sweep itself. This is adequate for a zero-parameter getter.

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 action ('Get the link') and adds necessary context. No wasted words.

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 simplicity (zero params, no output schema), the description is complete: it states what is returned (a link) and the purpose of that link. No additional behavioral or contextual information is necessary for an agent to correctly invoke the tool.

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 accepts zero parameters, and the schema already reflects this. The description does not need to add parameter details. Baseline for zero params is 4, and the description is consistent with that.

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 returns a link to the Sweep Generator tool and explains its purpose (testing audio equipment across frequencies). It distinguishes this from sibling get_tone_url (which likely provides a tone link) and recommend_frequency (which recommends a frequency).

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 the tool: when a link to a frequency sweep tool is needed. It does not explicitly mention alternatives, but the context is clear and sibling tool names imply different use cases, so it earns a 4.

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 output type (direct URL), the operational range (1-20000 Hz), and the external service (Online Tone Generator). This is sufficient for a simple, read-like operation and adds context beyond just the name.

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, the resource, and the scope without any unnecessary words. It is concise and immediately understandable.

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 (one parameter, no output schema), and the description fully explains its purpose and the key constraint (frequency range). The agent has enough information to select and invoke the tool correctly without needing further 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 already fully documents the single parameter 'frequency' with min/max and an example. The description redundantly mentions the 1-20000 Hz range but adds no new semantic information beyond the schema. With 100% schema coverage, the baseline score of 3 is appropriate.

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 'Get', identifies the resource as 'a direct URL', and clarifies the scope as 'a specific audio frequency (1-20000 Hz)'. This clearly distinguishes it from siblings like get_sweep_tool (which likely produces a sweep) and recommend_frequency (which recommends instead of generating).

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 when you need a direct playable URL for a single tone, as opposed to a sweep or recommendation. It does not explicitly mention when not to use it, but the purpose is unambiguous enough for an agent to infer appropriate usage.

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 burden of behavioral disclosure. It states that the tool returns recommended frequencies and links, but does not elaborate on whether it is read-only, requires authentication, or has any side effects. The behavior is clear at a basic level but lacks depth.

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, front-loaded sentence that communicates the tool's purpose and output without unnecessary detail. 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?

Given the simplicity (one parameter, no output schema), the description adequately covers the tool's behavior by stating it returns recommended frequencies and direct generation links. However, it does not specify the format or structure of the links or frequencies, which a small gap but not critical for this tool's complexity.

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%, as the 'useCase' parameter has a fully described enum. The description mentions 'specific use case' but adds no extra meaning beyond what the schema already provides, so the baseline of 3 applies.

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 provides recommended frequencies for a specific use case and includes direct generation links. This distinguishes it from sibling tools like get_tone_url and get_sweep_tool, which are likely for generating tones directly rather than providing recommendations.

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 usage for a specific use case but does not explicitly state when to prefer this over alternatives or provide exclusions. The enum of use cases gives context, but there is no explicit guidance on tool selection.

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