aaron-marketing-skills is a collection of 120 AI-agent skills covering marketing work such as brand narrative, search optimization, social media, email, advertising, influencer campaigns, and launches. Marketers and agent users can install it as a plugin, use its portable skills, or run its described bot team. The catalogue entries are components of this marketing workflow.
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.
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skillsWrote 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/commands/aaron-he-zhu/aaron-marketing-skills/email)<a href="https://agentmods.dev/commands/aaron-he-zhu/aaron-marketing-skills/email"><img src="https://agentmods.dev/badge/commands/aaron-he-zhu/aaron-marketing-skills/email/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/commands/aaron-he-zhu/aaron-marketing-skills/email"><img src="https://agentmods.dev/badge/commands/aaron-he-zhu/aaron-marketing-skills/email.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00050 | $0.01192 |
| Opus 5 | $0.00025 | $0.00596 |
| Sonnet 5 | $0.00010 | $0.00238 |
| Haiku 4.5 | $0.00005 | $0.00119 |
Grade A, and why
email 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 13d 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Command
Run the email-marketing lifecycle along the SEND loop (Setup → Engage → Nurture → Deliver). Skills score on the SEND framework and operate from the user's own-account manual export — keyed ESP APIs (Klaviyo, Mailchimp, HubSpot, Customer.io) are never required. The discipline is use-case-agnostic: the same skills serve B2C lifecycle/ecommerce, B2B cold outbound, and newsletter/creator programs; the goal you name selects the SEND typed profile.
Route
Infer the SEND-loop phase from the goal (or honor --phase) and route to the matching skill:
- Setup — deliverability-qa (SPF/DKIM/DMARC/BIMI auth, reputation, inbox-placement, spam-content — the S1 pre-flight), list-segment-builder (behavioral + lifecycle-stage segments + suppression), list-growth-designer (acquisition strategy + compliant opt-in capture-flow spec), list-hygiene-monitor (scheduled list-health / decay watch); consult consent-registry's per-subject records (
memory/consent/) for lawful basis and suppression before building or sending - Engage — email-creative-builder (subject/preheader/body/CTA, message-matched to the landing page), subject-line-lab (subject variants + pre-score + truncation/spam check), email-render-builder (responsive HTML + dark-mode + cross-client QA), dynamic-content-personalizer (merge tags + conditional blocks per segment); read approved wording from the claims projection and submit
[needs source]items as claims proposals; reuse audience-mapper for persona / lifecycle-stage definition - Nurture — email-sequence-designer (welcome / cart / post-purchase / win-back flows + frequency governance), newsletter-monetization-planner (paid-sub / sponsorship / referral economics), preference-frequency-manager (preference center + frequency opt-down ladder), reactivation-specialist (win-back + re-permission + list sunset); reuse landing-optimizer for the post-click page
- Deliver — send-experiment-designer (A/B / send-time / hold-out design + significance read), inbox-placement-monitor (post-send seed-list inbox-vs-spam trend), cold-outbound-sequencer (B2B cold sequence + reply-triage branching + domain warmup), then email-quality-auditor (the EQS gate + pre-send go/no-go; S2/N1 judged against consent-registry, D1 against offer-claims-registry); reuse roi-calculator / report-generator / performance-analyzer
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.
- 13d ago First seen · 38 lines · 50 tokens per session scan A a363a4596e00
email is a command published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 1,192 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 2026-08-30.
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