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seandkendall

productivity-mcp

by seandkendall

read_email

Fetch the full content of a specific email message from your account. Get the body in plaintext for easy reading or raw HTML for formatting.

Instructions

Fetch a single message with its body.

Args: message_id: Provider message id from list_emails. account: Account label (see list_email_accounts). folder: Folder / label. Default INBOX. format: 'text' (default) renders HTML bodies to plaintext — the LLM-friendly default. 'html' keeps raw HTML. 'both' returns a body_html field alongside plaintext body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
message_idYes
accountNo
folderNoINBOX
formatNotext

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description explains the format parameter's behavior (HTML-to-plaintext conversion) and defaults, which is helpful. However, it does not explicitly state that the operation is read-only (no annotation provided), nor does it mention authentication or other behavioral traits beyond what is shared.

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?

The description is concise with a one-sentence summary followed by a structured parameter list. Every part is informative without redundancy, fitting the content in minimal space.

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 the existence of an output schema (not needing return value details) and 4 input parameters, the description covers input semantics well. It lacks any mention of error handling or limits, but for a simple fetch tool this is sufficient.

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?

The description adds significant meaning to all 4 parameters, covering message_id source, account source, folder default, and format options with clear explanations. Since schema_description_coverage is 0%, this extra detail is crucial for correct invocation.

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 opens with 'Fetch a single message with its body,' clearly stating the verb and resource. It distinguishes from siblings like list_emails (which lists multiple) and other tools that modify or delete 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 guides the agent to obtain `message_id` from `list_emails` and `account` from `list_email_accounts`, providing cross-references to sibling tools. However, it does not explicitly state when to use this tool versus alternatives or provide exclusions.

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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