Skip to main content
Glama

Update Email Properties

email_update
Idempotent

Update email properties such as read status, categories, importance, flag, and classification without changing the email content.

Instructions

✏️ Update email properties (requires user confirmation recommended)

Modifies properties like isRead status, categories, and flags without changing email content.

Examples: email_update(email_id, {"isRead": True}, account_id) email_update(email_id, {"categories": ["Important"]}, account_id)

Allowed update keys: isRead, categories, importance, flag, inferenceClassification.

Args: email_id: The email ID to update updates: Dictionary of properties to update account_id: Microsoft account ID

Returns: Updated email object

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_idYes
updatesYes
account_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate idempotent and non-destructive. Description adds that user confirmation is recommended and specifies allowed update keys, adding behavioral context beyond annotations.

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 icon, summary, examples, allowed keys, args, and returns. No fluff, efficient use of text.

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?

Covers inputs, allowed keys, examples, and user confirmation. Output schema exists and description mentions 'Updated email object', which is sufficient given the available output schema.

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?

With 0% schema description coverage, the description fully explains each parameter: email_id as 'The email ID to update', updates as a dictionary with allowed keys, and account_id as 'Microsoft account ID'. This adds significant meaning beyond schema names.

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?

Description clearly states the tool updates email properties like isRead, categories, and flags, and explicitly says it does not change email content. This distinguishes it from sibling tools like email_mark_read and email_flag.

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

Usage Guidelines3/5

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

Provides a note about user confirmation recommended and gives examples, but does not explicitly guide when to use this tool versus other email siblings like email_mark_read or email_add_category.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/robin-collins/m365-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server