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AIsa Agent Mail

Get Draft

get_agentmail_inbox_draft
Read-onlyIdempotent

Fetches one unsent draft in full: draft_id, inbox_id, client_id, labels, reply_to, to, cc, bcc, subject, preview, text, html, attachments, in_reply_to and references. Edit it with patch_agentmail_inbox_draft, send it with post_agentmail_inbox_draft_send.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draft_idYesID of draft.
inbox_idYesThe ID of the inbox.
AuthorizationYesBearer authentication

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the 'unsent draft' qualifier and 'in full' detail, which clarifies the scope beyond raw annotations but does not add behavioral context like error handling or pagination. With annotations handling the primary behavioral traits, a 3 is appropriate.

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 two sentences with no redundant content. The first sentence leads with the action and specifies the return fields, while the second succinctly points to related operations. It is front-loaded and every sentence earns its place, achieving excellent conciseness.

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?

The tool has an output schema, so return values are defined separately, and annotations cover safety, reducing the burden on the description. The description explains the tool's purpose and suggests next steps, covering the essential context for an agent. It lacks explicit error handling or edge cases, but for a simple fetch operation, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and each parameter (draft_id, inbox_id, Authorization) already has a clear description. The tool description does not add any additional parameter semantics; it merely lists the fields returned, which are separate from the input parameters. Since the schema fully documents the parameters, the description adds no value here, placing it at the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'fetches' and the resource 'one unsent draft in full', and enumerates the returned fields. It distinguishes from plural-fetch siblings by saying 'one' draft, though it doesn't explicitly differentiate from get_agentmail_draft, which may target drafts without inbox context. Overall, purpose is specific and unambiguous.

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?

The description implies usage for retrieving a single draft and suggests follow-up actions (edit/send), but it does not explicitly state when to use this tool over alternatives like get_agentmail_draft or get_agentmail_inbox_drafts, nor does it provide exclusions. The context is clear but not explicit, so it meets the 'implied usage' criterion without stronger guidance.

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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