email-ops

email-ops is a skill for Claude Code, Codex from ufy2024/AuC. It costs 50 tokens per session (863 once invoked), scanned A, original, MIT.

An email-handling workflow for sorting mail, preparing replies, sending messages, and checking that they appear in Sent.

In plain words
What is it for?
Use it to triage inboxes, draft or send email, verify sent messages, and follow up safely.
Why use it?
It helps prevent mistakes such as sending from the wrong account or claiming that an email was sent without confirmation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to triage inboxes, draft or send email, verify sent messages, and follow up safely.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ufy2024/auc/email-ops
View source ↗ ufy2024/AuC
About the project

AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.

ufy2024/AuC · 1,090 stars · on GitHub

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.

Any agent
npx skills add ufy2024/AuC --skill email-ops
Clone the repo
git clone --depth 1 https://github.com/ufy2024/AuC

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-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/ufy2024/auc/email-ops.svg)](https://agentmods.dev/skills/ufy2024/auc/email-ops)
Your own site
<a href="https://agentmods.dev/skills/ufy2024/auc/email-ops"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/email-ops.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 863 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 21
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
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 5.1 $0.00050 $0.00863
Opus 5 $0.00025 $0.00432
Sonnet 5 $0.00010 $0.00173
Haiku 4.5 $0.00005 $0.00086

Measured 5d ago against content hash 317fccd284bd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

email-ops 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 5d 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

auc/skill_library/bundled/email-ops/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Email Ops

Use this when the real task is mailbox work: triage, drafting, replying, sending, or proving a message landed in Sent.

This is not a generic writing skill. It is an operator workflow around the actual mail surface.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • brand-voice before drafting anything user-facing
  • investor-outreach for investor, partner, or sponsor-facing mail
  • customer-billing-ops when the thread is a billing/support incident rather than generic correspondence
  • knowledge-ops when the message or thread should be captured into durable context afterward
  • research-ops when a reply depends on fresh external facts

When to Use

  • user asks to triage inbox or archive low-signal mail
  • user wants a draft, reply, or new outbound email
  • user wants to know whether a mail was already sent
  • the user wants proof of which account, thread, or Sent entry was used

Guardrails

  • draft first unless the user clearly asked for a live send
  • never claim a message was sent without a real Sent-folder or client-side confirmation
  • do not switch sender accounts casually; choose the account that matches the project and recipient
  • do not delete uncertain business mail during cleanup
  • if the task is really DM or iMessage work, hand off to messages-ops

Workflow

1. Resolve the exact surface

Before acting, settle:

  • which mailbox account
  • which thread or recipient
  • whether the task is triage, draft, reply, or send
  • whether the user wants draft-only or live send

2. Read the thread before composing

If replying:

  • read the existing thread
  • identify the last outbound touch
  • identify any commitments, deadlines, or unanswered questions

If creating a new outbound:

  • identify warmth level
  • select the correct channel and sender account
  • pull brand-voice before drafting

3. Draft, then verify

For draft-only work:

  • produce the final copy
  • state sender, recipient, subject, and purpose

Read the full file on GitHub · 143 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. 5d ago First seen · 143 lines · 50 tokens per session scan A 317fccd284bd

Subscribe to this mod's changes

email-ops is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 863 once invoked, about $0.0003 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 2026-09-03.