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send_email

Destructive

Send email from your connected account: compose directly, use an existing draft, or reply to a message with automatic threading. Optionally schedule delivery.

Instructions

Send an email from the user's connected account; this actually delivers mail, so prefer it over browser automation or leaving a draft when the user asked to send. Three modes: direct (to + subject + body), sending an existing draft (draftId), or replying (replyToMessageId, optionally replyAll) where recipients, subject, and threading are derived from the original. Confirm with the user when intent is ambiguous. Add sendAt to any mode to schedule instead of sending now.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ccNoRecipients, each "Name <a@x.com>" or "a@x.com"
toNoRecipients, each "Name <a@x.com>" or "a@x.com"
bccNoRecipients, each "Name <a@x.com>" or "a@x.com"
sendAtNoSchedule delivery instead of sending now: ISO 8601 with timezone offset or Z (e.g. 2026-07-11T09:00:00-07:00). Fluxmail saves the message as a real draft in the mailbox and sends it at this time; the server must be running then (anything missed while it was down goes out at the next startup). Returns a scheduleId for list/cancel.
draftIdNoSend this existing draft
subjectNoDefaults to "Re: ..." when replying
bodyHtmlNoHTML body
bodyTextNoPlain-text body
replyAllNoWith replyToMessageId: reply to all original recipients
accountIdNoAccount to operate on. Optional when exactly one account is connected.
attachmentsNo
replyToMessageIdNoMessage being replied to; threads correctly and computes recipients if "to" is omitted
Behavior5/5

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

Beyond the destructiveHint annotation, the description details scheduling behavior (saves as draft, server dependency), reply threading, and default subject behavior. All key behavioral traits are disclosed.

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 three well-structured sentences: purpose, modes, and scheduling. Every sentence conveys critical information with no redundancy.

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

Completeness4/5

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

Covers all major behaviors and parameter interactions for a complex tool with 12 parameters. Minor omission: no mention of error handling or output, but the high schema coverage and clear mode descriptions compensate.

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

Parameters5/5

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

Despite high schema coverage (92%), the description adds significant value by explaining the three modes, how parameters relate (e.g., replyToMessageId computes recipients), and scheduling details, enabling correct invocation.

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

Purpose5/5

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

The description clearly states it sends an email, distinguishes from sibling tools like create_draft and browser automation, and enumerates three distinct modes (direct, draft, reply).

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises preferring this over browser automation or leaving a draft when the user asks to send, and instructs to confirm with the user when intent is ambiguous. This provides clear when-to-use and when-not-to-use guidance.

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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