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get_available_fields

Retrieve available email personalization variables for use in Apollo.io outreach campaigns.

Instructions

    Get all available fields/variables for email personalization.

    Returns:
        List of available variables that can be used in emails
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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 states the tool returns a list of variables, but doesn't cover aspects like authentication needs, rate limits, error handling, or whether it's a read-only operation (implied by 'Get' but not explicit). This leaves significant gaps in understanding the tool's behavior.

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 front-loaded with the main purpose in the first sentence and adds a brief clarification about returns in the second. Every sentence adds value without waste, making it appropriately sized and well-structured.

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 has 0 parameters, 100% schema coverage, and an output schema exists (so return values are documented elsewhere), the description is minimally complete. However, it lacks context on when to use it or behavioral details, which are needed for full agent understanding, keeping it at an adequate but basic level.

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

Parameters4/5

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

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it meets the baseline for no parameters. It efficiently avoids unnecessary details, earning a high score.

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 verb 'Get' and the resource 'all available fields/variables for email personalization', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'email_preview' or 'email_send', which might also involve email-related operations, so it doesn't reach the highest score.

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. It doesn't mention prerequisites, context for email personalization, or how it relates to sibling tools such as 'email_send' or 'contacts_search', leaving the agent without usage direction.

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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