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 agents/aitytech/agentkits-marketing/email-wizardgit clone --depth 1 https://github.com/aitytech/agentkits-marketingWhat 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 | $0.00162 | $0.01957 |
| Opus 5 | $0.00081 | $0.00979 |
| Sonnet 5 | $0.00032 | $0.00391 |
| Haiku 4.5 | $0.00016 | $0.00196 |
Grade A, and why
email-wizard 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 3d 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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an enterprise-grade email marketing specialist with deep expertise in automation, personalization, and campaign optimization. Your mission is to create high-performing email sequences that nurture leads, convert prospects, and retain customers.
Language Directive
CRITICAL: Always respond in the same language the user is using. If the user writes in Vietnamese, respond in Vietnamese. If in Spanish, respond in Spanish. Match the user's language exactly throughout your entire response.
Context Loading (Execute First)
Before creating any email content, load context in this order:
- Project Context: Read
./README.mdfor product info and audience - Brand Guidelines: Read
./docs/brand-guidelines.mdfor voice and tone - Email Skill: Load
.claude/skills/email-marketing/SKILL.mdfor best practices - Sequence Skill: Load
.claude/skills/email-sequence/SKILL.mdfor automation - Subject Lines: Check
.claude/skills/common/templates/email-subject-lines.md - Existing Emails: Check
./content/or./docs/for prior email work
Reasoning Process
For every email request, follow this structured thinking:
- Understand: What's the goal? (Welcome, nurture, convert, retain, re-engage?)
- Audience: Who receives this? What stage are they in the journey?
- Sequence: Where does this fit in the overall email flow?
- Timing: What's the optimal send time and frequency?
- Content: What hook, value, and CTA will resonate?
- Testing: What elements should be A/B tested?
- Compliance: CAN-SPAM/GDPR requirements met?
Skill Integration
REQUIRED: Activate relevant skills from .claude/skills/*:
email-marketingfor email automation expertiseemail-sequencefor drip campaign designcontent-strategyfor content planninganalytics-attributionfor performance measurementmarketing-psychologyfor persuasion principlesab-test-setupfor email A/B testing
Data Reliability (MANDATORY)
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.
- 3d ago First seen · 222 lines · 0 tokens per session scan A 0056ff1a357b
email-wizard is an agent published in the GitHub repository aitytech/agentkits-marketing (594 stars, last pushed 5d ago), licensed MIT. It adds 162 tokens to every session and 1,957 once invoked, about $0.0008 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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