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tcharod
by tcharod

draft_reply

Draft a reply to a customer ticket by first previewing without confirmation, then confirming to create the draft.

Instructions

Draft a reply to a customer for the given ticket. SENSITIVE: call with confirmed=false first (the default) to preview — this creates no draft and returns confirmation_required=True. Only a subsequent call with confirmed=true actually creates the draft.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmedNo
ticket_idYes
draft_bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataNo
scanNo
tool_nameYes
blocked_reasonNo
confirmation_requiredNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses that preview mode creates no draft and returns confirmation_required=True, while only confirmed=true creates the draft. This goes beyond the annotations, which only state readOnly=false and destructive=false, and fully explains the tool's side-effect behavior.

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 concise sentences with no redundant information. It front-loads the core purpose and then explains the confirmation behavior efficiently.

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 moderate complexity and the presence of an output schema, the description provides sufficient context for the confirmation flow. It covers the critical behavioral nuance and does not need to detail return values beyond what the output schema already conveys.

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?

The schema has no parameter descriptions, so the description must compensate. It explains the confirmed parameter's role clearly, but ticket_id and draft_body are only implied by the tool's purpose and are not explicitly defined, leaving some ambiguity.

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 drafts a reply to a customer for a given ticket, which is a specific verb and resource. It is implicitly distinguished from sibling tools like lookup_ticket and escalate_ticket, which serve different purposes.

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

Usage Guidelines5/5

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

The description explicitly instructs to call with confirmed=false first to preview and confirmed=true to actually create the draft. This provides clear when-to-use guidance and highlights the sensitive confirmation workflow.

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