marketing_get_voice_of_customer

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

No annotations are provided, so the description carries full behavioral disclosure burden. It describes a method but does not specify what the tool actually returns (e.g., copy text, analysis), nor does it mention any side effects, authentication needs, or rate limits. The behavior is vaguely implied as informational but lacks explicit details.

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 only three sentences, front-loaded with the core concept, and contains no wasted words. It efficiently conveys the tool's purpose and usage guidance.

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 has no parameters and no output schema, the description is moderately complete. It tells what the tool does and when to use it, but it does not explain the format of the output or any prerequisites. For a knowledge tool, this is adequate but could be more explicit about what the agent receives after 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 tool has zero parameters, so the schema coverage is trivially 100%. According to the calibration, 0 parameters yields a baseline of 4. The description does not need to add parameter context, but it could mention the absence of inputs; still, the baseline 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's purpose: harvesting customers' exact words from reviews, support, calls, and surveys to turn them into copy. It uses specific verbs ('harvest', 'turn') and distinguishes itself from sibling tools like marketing_get_voice by positioning itself as the first step before writing.

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 explicitly says 'Use FIRST, before writing anything,' providing clear context for when to use the tool. However, it does not explicitly list when not to use it or mention specific alternatives among siblings, though the positioning as a first step implicitly guides usage.

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