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List Emails

email_list
Read-onlyIdempotent

Lists recent emails from a specified mailbox folder, returning subject, sender, date, size, and attachment info. Supports caching for performance.

Instructions

📖 List emails from a mailbox folder (read-only, safe for unsupervised use)

Returns recent emails with subject, sender, date, size, and attachment info.

Caching: Results are cached for 2 minutes (fresh) / 10 minutes (stale). Use force_refresh=True to bypass cache and fetch fresh data.

Args: account_id: Microsoft account ID folder: Folder name (inbox, sent, drafts, deleted, junk, archive) folder_id: Direct folder ID - takes precedence over folder name limit: Maximum emails to return (1-200, default: 10) include_body: Whether to include email body content (default: True) use_cache: Whether to use cached data if available (default: True) force_refresh: Force refresh from API, bypassing cache (default: False)

Returns: List of email messages with metadata and optionally body content. Each message includes _cache_status and _cached_at fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idYes
folderNo
folder_idNo
limitNo
include_bodyNo
use_cacheNo
force_refreshNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations (readOnlyHint, etc.), the description adds caching details (2 min fresh, 10 min stale), return field information, and parameter behavior (force_refresh). No contradictions.

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?

The description is well-structured with sections (Returns, Caching, Args) and an emoji for visual cue. It is slightly verbose but each sentence adds value. Front-loading with purpose is effective.

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

Completeness5/5

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

Given 7 parameters, output schema presence, and sibling tools, the description covers all aspects: function, parameters, caching, return format, and safety. No gaps remain.

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 coverage is 0% but the description's Args section thoroughly explains each parameter: account_id, folder (with allowed values), folder_id, limit (with range), include_body, use_cache, force_refresh. This adds meaning far beyond the 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 'List emails from a mailbox folder' with a specific verb and resource. It distinguishes from siblings like email_get (single email) and email_send. The emoji and 'read-only' further clarify purpose.

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 indicates this is 'read-only, safe for unsupervised use' and explains caching behavior. However, it does not explicitly contrast with alternatives like search_emails or when not to use it, slightly reducing clarity.

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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