email-draft

email-draft is a skill for Claude Code, Codex from jamesol-msft/claude-email-draft-plugin. It costs 46 tokens per session (5,917 once invoked), scanned A, original, MIT.

An email-reply drafting workflow that searches for an email, analyses its context, and generates a reply matching the recipient's communication style.

In plain words
What is it for?
Finding emails by message ID or natural-language search, identifying their main points, and creating executive-style draft replies through the connected mail service.
Why use it?
It reduces the work of finding the right message, understanding it, and writing a suitably personalised response.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jamesol-msft/claude-email-draft-plugin/email-draft
Any agent
npx skills add jamesol-msft/claude-email-draft-plugin --skill email-draft
Clone the repo
git clone --depth 1 https://github.com/jamesol-msft/claude-email-draft-plugin

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for email-draft

README.md
[![agentmods](https://agentmods.dev/badge/skills/jamesol-msft/claude-email-draft-plugin/email-draft.svg)](https://agentmods.dev/skills/jamesol-msft/claude-email-draft-plugin/email-draft)
Your own site
<a href="https://agentmods.dev/skills/jamesol-msft/claude-email-draft-plugin/email-draft"><img src="https://agentmods.dev/badge/skills/jamesol-msft/claude-email-draft-plugin/email-draft.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,917 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.05917
Opus 5 $0.00023 $0.02959
Sonnet 5 $0.00009 $0.01183
Haiku 4.5 $0.00005 $0.00592

Measured 4d ago against content hash 59391977bfef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

email-draft scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/email-draft/SKILL.md · 834 lines

How it starts

The opening of the file, as written. The whole thing — 834 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Email Draft Generator

Purpose

Intelligent email draft generator that creates high-quality, style-matched draft replies using a 3-stage workflow. Combines email search, context analysis, and executive writing style profiles to generate draft replies that match the recipient's communication preferences.

Key Features:

  • Email Search: Natural language search with fallback strategies
  • Context Analysis: Extracts key points and themes from original email
  • Style Matching: 6-level fallback algorithm with 4 executive profiles
  • Draft Generation: Claude-generated drafts matching recipient style
  • MCP Integration: Uses agent365-mail-proxy for email operations

MCP Servers Used

  • agent365-mail-proxy - Email search, retrieval, draft creation (included in plugin package)

Mandatory Workflow: 3-Stage Process

Stage 1: Email Search & Discovery

Purpose: Locate the email requiring a reply using natural language search.

Search Strategies (3 strategies with fallback):

  1. Direct Email ID (Highest confidence: 100%)

    • User provides exact message ID
    • Fastest, no ambiguity
    • Example: email_id: "AAMkAGI2T..."
  2. Natural Language Search (High confidence: 85-95%)

    • User provides search query with sender/subject/keywords
    • Uses Agent 365 natural language processing
    • Example: query: "email from Charles about Q4 budget"
  3. Most Recent Email (Fallback: 50-70%)

    • Returns most recent email from inbox
    • Used when search returns no results
    • Example: query: "latest email"

MCP Tool Integration:

# Strategy 1: Direct Email ID
if email_id:
    message = mcp__agent365_mail_proxy__get_message(id=email_id)

# Strategy 2: Natural Language Search
else:
    results = mcp__agent365_mail_proxy__search_messages(
        query=user_query,  # e.g., "emails from Sarah about budget"
        top=5
    )
    # Parse results and select most relevant match
    message = results[0] if results else None

# Strategy 3: Fallback to latest
if not message:
    results = mcp__agent365_mail_proxy__search_messages(
        query="recent emails",
        top=1
    )
    message = results[0] if results else None

Read the full file on GitHub · 834 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 834 lines · 46 tokens per session scan A 59391977bfef

Subscribe to this mod's changes

email-draft is a skill published in the GitHub repository jamesol-msft/claude-email-draft-plugin (0 stars, last pushed 6mo ago), licensed MIT. It adds 46 tokens to every session and 5,917 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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