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List AI reply drafts

list_reply_drafts
Read-only

Lists AI-suggested reply drafts awaiting review, newest first, 20 per page. Each draft answers the inbound reply referenced by inReplyToEmailId. Nothing here has been sent: a draft stays a draft until a human sends it from the app or send_reply_draft is called. Edit one first with update_reply_draft if the wording needs work.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, starting at 1
limitNoPage size (default 20, max 200)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), but the description adds genuinely useful state semantics: drafts are unsent and remain drafts until a human acts, plus ordering and page-size behavior. This is real context beyond the 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?

Four sentences, purpose front-loaded, and each clause earns its place by clarifying the draft lifecycle or the follow-up tools. No filler or restatement of the tool name.

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?

With no output schema, the description could say more about what a draft object contains (fields returned), but it does convey the key semantics: what a draft is, its ordering, pagination, and the inReplyToEmailId relationship. Adequate for correct invocation, slightly light on return content.

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

Parameters4/5

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

Schema coverage is 100%, so the schema documents page and limit. The description still adds the sort order ('newest first') and reinforces the default page size ('20 per page'), which the schema only partially conveys. It adds modest but non-redundant meaning.

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?

States a specific verb ('Lists') and resource ('AI-suggested reply drafts awaiting review'), and frames the draft lifecycle so an agent distinguishes it from list_replies (inbound messages) and the send/update siblings. The scope is unambiguous.

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?

Explains the review context and names the downstream actions (send_reply_draft to send, update_reply_draft to edit), effectively telling the agent where this fits in the workflow. It does not explicitly state when to prefer this over list_replies, so it falls short of full when/when-not routing.

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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