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 skills add vasilyu1983/AI-Agents-public --skill software-email-engineeringgit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/software-email-engineering)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-email-engineering"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-email-engineering/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-email-engineering"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-email-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Data Exfiltration · line 184 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 5.1 | $0.00032 | $0.06687 |
| Opus 5 | $0.00016 | $0.03343 |
| Sonnet 5 | $0.00006 | $0.01337 |
| Haiku 4.5 | $0.00003 | $0.00669 |
Grade A, and why
software-email-engineering 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 9d 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 — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Transactional Email Engineering
Build reliable email systems that reach the inbox.
Quick Reference
| Need | Recommended Options |
|---|---|
| Transactional ESP | Resend (modern DX), Postmark (deliverability), SendGrid (scale), AWS SES (cost) |
| Email templates | React Email (React components), MJML (responsive markup), Maizzle (Tailwind for email) |
| HTML email testing | Litmus (now part of Validity; pricing jumped sharply post-acquisition), Email on Acid, Parcel (free) |
| Deliverability setup | SPF, DKIM, DMARC, dedicated sending domain |
| Inbound email | SendGrid Inbound Parse, Postmark Inbound, AWS SES receiving |
| Email queue | Background job + idempotent send, dead letter queue for failures |
| Template preview | React Email preview server, Maizzle dev server |
| Tracking | Open tracking (pixel), click tracking (link wrapping), unsubscribe handling |
When to Use This Skill
- Choosing a transactional email provider for an application
- Building email sending infrastructure (queues, retries, idempotency)
- Developing HTML email templates that render across clients
- Setting up SPF, DKIM, and DMARC for a sending domain
- Implementing inbound email processing (reply-by-email, email-to-ticket)
- Debugging deliverability issues (bounces, spam folder placement, authentication failures)
When NOT to Use This Skill
- Marketing email campaigns and automation →
marketing-email-automation - Email deliverability for marketing (list hygiene, segmentation) →
marketing-email-automation - Backend API design and service architecture → software-backend
- Background job infrastructure (generic) → software-backend
- Push notifications and mobile messaging → software-mobile
- Real-time in-app notifications → software-realtime
Workflow
- Confirm the email job: provider choice, sending infrastructure, template work, deliverability, or inbound handling.
- Route lifecycle-marketing, generic backend, or mobile-notification work to the adjacent skill when email engineering is not the main problem.
- Choose the provider and template approach from the decision tree.
- Apply the relevant architecture, authentication, retry, rendering, and inbound-processing guidance.
- Verify current provider capabilities, limits, and policies through the navigation references before final advice.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 339 lines · 32 tokens per session scan A e670d968642e
software-email-engineering is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 32 tokens to every session and 6,687 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 2026-09-03.
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