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.
npx agentmods add skills/jamesol-msft/claude-email-draft-plugin/email-draftnpx skills add jamesol-msft/claude-email-draft-plugin --skill email-draftgit clone --depth 1 https://github.com/jamesol-msft/claude-email-draft-pluginWrote 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.
[](https://agentmods.dev/skills/jamesol-msft/claude-email-draft-plugin/email-draft)<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>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.
| Model | Per session | Once 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 |
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.
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):
-
Direct Email ID (Highest confidence: 100%)
- User provides exact message ID
- Fastest, no ambiguity
- Example:
email_id: "AAMkAGI2T..."
-
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"
-
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
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.
- 4d ago First seen · 834 lines · 46 tokens per session scan A 59391977bfef
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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