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get_todays_emails

Retrieve all emails received today from a specified mailbox, sorted by date with newest first, using environment variables for default account and mailbox settings.

Instructions

Get all emails received today from a mailbox.

Args: account: Account name. Uses JXA_MAIL_DEFAULT_ACCOUNT env var or first account if not specified. mailbox: Mailbox name. Uses JXA_MAIL_DEFAULT_MAILBOX env var or "Inbox" if not specified.

Returns: List of today's emails sorted by date (newest first).

Example: >>> get_todays_emails("Work") [{"subject": "Urgent: Review needed", "sender": "team@work.com", ...}]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
mailboxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses the sorting behavior ('sorted by date newest first') and return format ('List of today's emails'), which is valuable. However, it doesn't mention permissions needed, rate limits, pagination, or what happens with invalid account/mailbox values.

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?

Well-structured with purpose statement, parameter explanations, return description, and example. Every sentence earns its place. The information is front-loaded with the core purpose first, followed by details.

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?

Given 2 parameters with 0% schema coverage and an output schema exists, the description does an excellent job explaining parameters and return behavior. However, as a read operation with no annotations, it could benefit from mentioning safety (non-destructive) or error handling for completeness.

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 description coverage is 0%, so the description must compensate fully. It provides detailed semantics for both parameters: account (defaults from env var or first account) and mailbox (defaults from env var or 'Inbox'). The example further clarifies usage. This adds significant value beyond the bare schema.

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 the tool's purpose with specific verb ('Get'), resource ('all emails received today'), and scope ('from a mailbox'). It distinguishes from siblings by focusing on today's emails only, unlike get_emails (general), get_flagged_emails, get_unread_emails, or search_emails.

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?

The description provides clear context about when to use this tool (for today's emails), but doesn't explicitly state when not to use it or name alternatives. It implies usage for today's emails but doesn't compare with siblings like get_emails (date-range) or search_emails (keyword-based).

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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