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send_email

Send emails from a configured Zoho Mail address to recipients with custom subjects and HTML content.

Instructions

Send an email from the configured ZOHO_SENDER address

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesRecipient email address
subjectYesEmail subject
contentYesEmail body — HTML is supported
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 mentions the sender address configuration, which adds some context about authentication needs, but fails to cover critical traits: it doesn't specify whether this is a synchronous or asynchronous operation, potential rate limits, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 front-loads the core purpose without unnecessary words. Every element ('Send an email', 'from the configured ZOHO_SENDER address') earns its place by clarifying scope and constraints. There's zero waste or redundancy, making it highly concise and well-structured for quick comprehension.

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

Completeness2/5

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

Given the complexity of an email-sending tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., delivery confirmation, error responses), usage context, and output expectations. While the schema covers parameters well, the overall context for safe and effective use is insufficient, especially for a mutation operation.

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?

The schema description coverage is 100%, with clear descriptions for all three parameters (to, subject, content). The description adds no parameter-specific information beyond what the schema provides, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('Send an email') and specifies the resource ('from the configured ZOHO_SENDER address'), making the purpose immediately understandable. It distinguishes from siblings like list_inbox or read_email by focusing on sending rather than retrieving emails. However, it doesn't explicitly differentiate from potential non-sibling alternatives like 'send_bulk_email' or 'schedule_email', which prevents a perfect 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 sibling tools like search_emails for finding emails before sending, or specify prerequisites such as needing a configured sender address. There's no indication of when not to use it (e.g., for bulk operations) or contextual triggers, leaving usage entirely implicit.

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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