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read-email

Read-only

Retrieve email content or forensic headers by ID. Choose from full message body, headers, or security-relevant details with customizable verbosity.

Instructions

Read a single email by id (read-only). Default: returns the full message body (HTML stripped to text by default), subject, from/to/cc, receivedDateTime, conversationId, attachments metadata, and webLink as Markdown. With headersMode: true: returns RFC-822 forensic headers instead (DKIM, SPF, DMARC, Received chain, Message-ID, Authentication-Results) — pair with importantOnly: true for the security-relevant subset, groupByType: true for category-bucketed view, or raw: true for JSON instead of Markdown. With includeHeaders: true (non-headers-mode): adds basic headers alongside body. Use outputVerbosity (minimal/standard/full) to control field count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesID of the email to read
rawNoReturn raw JSON instead of Markdown (headersMode only, default: false)
groupByTypeNoGroup headers by category (headersMode only, default: false)
headersModeNoReturn forensic headers instead of email content (default: false)
importantOnlyNoShow only important headers (headersMode only, default: false)
includeHeadersNoInclude basic headers alongside email content (default: false)
outputVerbosityNoOutput detail level (default: standard)
Behavior5/5

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

Annotations already declare readOnlyHint=true. The description adds extensive behavioral detail: HTML stripping, Markdown output, default field set, mode-specific outputs (headers, raw JSON, grouping, verbosity levels). 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 a single dense paragraph but is front-loaded with the core purpose. It efficiently packs many details but could benefit from bullet points or clearer separation of modes. No unnecessary words.

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 the complexity (7 parameters, conditional behaviors, no output schema), the description covers all significant use cases: default read, headers mode, important-only, grouping, raw output, and verbosity. It lists return fields comprehensively.

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 100%, but the description adds crucial context: it explains conditional interactions (e.g., headersMode changes output entirely, importantOnly works with headersMode, raw only for headersMode) and default values for each parameter. This goes beyond schema descriptions.

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 reads a single email by ID (read-only) and lists the returned fields (subject, from/to/cc, etc.). It distinguishes from siblings like send-email or update-email through its name and read-only nature.

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 explains when to use different modes (headersMode for forensic headers, importantOnly for security-relevant subset, etc.) and default behavior. It does not explicitly contrast with siblings but provides enough context for appropriate use.

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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