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list_answers_for_application

Retrieve demographic survey answers for a specific application in Greenhouse ATS to support diversity tracking and compliance reporting.

Instructions

List all demographic survey answers submitted for a specific application.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
application_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions listing answers but lacks details on behavioral traits such as pagination, rate limits, authentication needs, or what happens if the application_id is invalid. This leaves gaps for an AI agent to understand operational constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter) and the presence of an output schema, the description is somewhat complete but lacks behavioral context. Without annotations, it should ideally mention more about the operation's safety or limitations, though the output schema reduces the need to explain return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description adds meaning by clarifying that 'application_id' is required to list answers for a specific application. However, it does not provide format details or constraints beyond what the schema's type and title imply, resulting in minimal compensation for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all') and resource ('demographic survey answers submitted for a specific application'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list_answers' or 'list_answers_for_question', which could cause confusion about scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 (e.g., 'list_answers' or 'list_answers_for_question'), nor does it mention prerequisites or exclusions. It only specifies the required parameter without contextual usage advice.

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

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