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isityael

Apple Mail MCP Server

by isityael

delete_emails

Move emails matching filters (subject, sender, or age) to Trash. Dry-run by default to preview changes before actual deletion.

Instructions

Soft-delete emails (move to Trash) matching filters, with safety features.

IMPORTANT: dry_run=True by default -- shows what WOULD be deleted without acting. Set dry_run=False to actually move emails to Trash.

At least one filter (subject_keyword, sender, or older_than_days) is required. Emails are moved to Trash, never permanently deleted.

Args: account: Account name (e.g., "Gmail", "Work") subject_keyword: Optional keyword to filter emails by subject sender: Optional sender email/name to filter by older_than_days: Only affect emails older than N days mailbox: Source mailbox to search in (default: "INBOX") max_emails: Maximum number of emails to delete (safety limit, default: 25) dry_run: If True (default), only preview what would be deleted

Returns: List of affected email subjects and count

User Preferences: {"workflow": "default", "notifications": "enabled"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
senderNo
accountYes
dry_runNo
mailboxNoINBOX
max_emailsNo
older_than_daysNo
subject_keywordNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses soft-delete behavior, dry_run safety mode, max_emails safety limit, and that emails are never permanently deleted. Some minor details omitted (e.g., what happens on error), but overall transparent.

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

Conciseness4/5

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

Well-structured with a short intro, important note, arg list, and return description. Slightly verbose due to the 'Args' enumeration and user preferences JSON, but still efficient. Every sentence adds value.

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 purpose, parameters, return value ('List of affected email subjects and count'), and safety behavior. Since an output schema exists, detailed return format is not required. The description is complete for an agent to understand and invoke the tool.

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?

Schema has 0% description coverage for parameters. The description's 'Args' section explains each parameter's purpose and constraints, compensating fully. For example, it clarifies that `older_than_days` filters by age and `dry_run` defaults to True.

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 'Soft-delete emails (move to Trash) matching filters', identifying the specific action (soft-delete) and resource (emails). It distinguishes from siblings like archive_emails and manage_trash by focusing on deletion with filters.

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

Usage Guidelines4/5

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

Provides explicit guidance: dry_run=True by default, at least one filter required, and emails are moved to Trash, not permanently deleted. It does not directly contrast with sibling tools but gives clear usage constraints and safety features.

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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