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send_email

Send an email to an employee with a subject and body, enabling HR agents to deliver notifications, approvals, or updates directly within automated workflows.

Instructions

Send an email to an employee.
Args:
    to_email: str
    subject: str
    body: str
Returns:
    str

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
subjectYes
to_emailYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description is the only source for behavioral disclosure. It only states that an email is sent and that the return type is str, but it does not disclose whether the action is irreversible, whether it has external side effects, whether permissions are needed, or what happens on failure.

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

Conciseness3/5

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

The opening sentence is concise and front-loaded. However, the 'Args' and 'Returns' block largely duplicates the structured schema, adding little value and making the description slightly redundant.

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?

Although the tool is simple, the description leaves important operational gaps: it does not say whether the recipient must be an existing employee, how the email address can be obtained, or what the returned string means. The existence of an output schema reduces the return-value burden, but it does not fill the missing usage and behavioral context.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate by explaining parameter meaning. It merely repeats the parameter names and types already present in the schema (to_email, subject, body) without adding constraints, format expectations, or relationships between parameters.

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 first sentence clearly states a specific action (send) and resource (email), with the recipient scope being an employee. This is enough to distinguish the tool from siblings like get_leave_balance or create_ticket, although it does not explicitly discuss edge cases or alternatives.

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?

No when-to-use or when-not-to-use guidance is provided. The description does not mention prerequisites such as looking up an employee's email address, nor does it differentiate this from potentially similar workflows like creating a ticket or scheduling a meeting. The agent must infer usage entirely from the verb 'send' and the tool name.

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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