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/agricidaniel/claude-email/email-sequencenpx skills add AgriciDaniel/claude-email --skill email-sequencegit clone --depth 1 https://github.com/AgriciDaniel/claude-emailWrote 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/agricidaniel/claude-email/email-sequence)<a href="https://agentmods.dev/skills/agricidaniel/claude-email/email-sequence"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-email/email-sequence.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 5.1 | $0.00082 | $0.03013 |
| Opus 5 | $0.00041 | $0.01507 |
| Sonnet 5 | $0.00016 | $0.00603 |
| Haiku 4.5 | $0.00008 | $0.00301 |
Grade A, and why
email-sequence 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 6d 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 — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Sequence Designer
Designs complete email automation sequences with strategic timing, persuasive copy, and conditional logic.
Quick Reference
| Sequence Type | Emails | Duration | Best For |
|---|---|---|---|
| Welcome Series | 4-6 | 14 days | New subscribers |
| Nurture | 6-10 | 6-10 weeks | Education, engagement |
| Re-engagement | 3-5 | 28 days | Inactive subscribers |
| Abandoned Cart | 3 | 3 days | E-commerce recovery |
| Post-Purchase | 4-6 | 30 days | Customer experience |
| Review Request | 1-2 | 1-24 hours | Social proof |
| Custom | Variable | Variable | Specific goals |
Execution Protocol
Step 1: Load Context
Read the business profile for context:
email-profile.md(project root)
Load reference files for frameworks and benchmarks:
references/copy-frameworks.mdreferences/benchmarks.md
Step 2: Gather Sequence Requirements
Ask the user:
- Sequence type: welcome, nurture, re-engagement, abandoned-cart, post-purchase, review-request, or custom
- If custom: goal, trigger event, desired email count, preferred cadence, tone
Confirm business context from profile:
- Industry
- Target audience
- Brand voice
- Primary offer/product
Step 3: Design Sequence Architecture
Based on sequence type, define:
- Total number of emails
- Timing between emails
- Framework assignment per email
- Conditional logic rules
- KPI targets
Step 4: Generate Each Email
For each email in sequence, create:
- Position and timing: Email X, Day Y or Hours after trigger
- Subject lines: 3 variants with scores (60-100)
- Preheader text: 30-80 characters
- Email body: Full copy following assigned framework
- CTA: Button text and link placeholder
- Conditional logic: What happens based on engagement
Step 5: Add Implementation Guidance
Include:
- Platform setup notes
- A/B test recommendations
- KPI benchmarks for this sequence type
- Segment considerations
Sequence Type Templates
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.
- 6d ago First seen · 393 lines · 82 tokens per session scan A d94d118b9218
email-sequence is a skill published in the GitHub repository AgriciDaniel/claude-email (118 stars, last pushed 3mo ago), licensed MIT. It adds 82 tokens to every session and 3,013 once invoked, about $0.0004 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.
Other skills, from other repositories
ads-audit
Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform…
ads-amazon
Audit Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN advertising, Amazon DSP, or retail-media…
ads-apple
Audit Apple Ads measurement, AdServices and AdAttributionKit, campaign and keyword structure, Search Match, App Store placements, custom product pages, bidding, budgets, MMP reconciliation, and policy. Use for Apple Ads, Apple Search Ads, App Store ads, Search Match, custom product pages, AdServices, or Apple…
ads-google
Audit Google Ads measurement, Search, Shopping, Performance Max, Demand Gen, YouTube-linked inventory, keywords and search terms, negative-keyword generation or review, creative assets, bidding, budgets, settings, and policy. Use for Google Ads, AdWords, Search campaigns, search terms reports, broad negatives…
ads-landing
Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked…
ads-research
Refresh Claude Ads platform, API, policy, regulation, benchmark, issue, pull-request, fork, and repository evidence. Use for ads research refresh, expired refreshdue dates, stale API or platform claims, reverify-or-demote decisions, release-current claim validation, ecosystem review, current platform changes, or…