Email Lifecycle logo

Email Lifecycle

Organization
hyperfx-ai
email-lifecycle

Plan, build, and run lifecycle email programs through the Hyper MCP — welcome / onboarding, nurture, re-engagement, win-back, and abandoned-cart sequences across whichever provider fits (Klaviyo for ecommerce, Resend for SaaS / dev tools, Beehiiv for newsletters, Gmail for low-volume ops). Use when the user wants to build an email sequence, set up a welcome flow, recover lapsed users, send a broadcast, manage a list / audience / segment, or asks about lifecycle / drip / nurture campaigns.

Overview

Publisherhyperfx-ai
Repositorymarketing-skills
Skill nameemail-lifecycle
Stars
107
Forks
21
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hyperfx-ai on GitHub. Read the source before you install it.

Installation

Install the Email Lifecycle AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/email-lifecycle
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hyperfx-ai/marketing-skills.git /tmp/marketing-skills
mkdir -p .claude/skills
cp -r /tmp/marketing-skills/skills/email-lifecycle .claude/skills/email-lifecycle
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Email Lifecycle in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Email Lifecycle on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Email Lifecycle is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Email Lifecycle

End-to-end lifecycle email — pick the right provider for the job, build the audience, draft the sequence, launch, and measure. Cross-provider patterns at the top; provider-specific tool calls below.

Out of scope — defer to other skills

RequestSend them to
Cold outbound to people who haven't opted incold-email-outreach
Generating images for email creativesimage-generation
Generating ad creatives that run alongside the lifecycle programad-creative-generation
SEO research / blog content for the newsletterseo-research

Requirements

  • Hyper MCP installed and connected. https://app.hyperfx.ai/mcp
  • At least one of these providers connected at https://app.hyperfx.ai/apps:
    • Klaviyo — ecommerce, Shopify-heavy lists, behavioral triggers off purchase / browse data
    • Resend — product-led / SaaS / dev tools, transactional + lifecycle on the same domain
    • Beehiiv — newsletters, paid-tier subscriptions, content-driven lists
    • Gmail — small / personal lists, founder-mode broadcasts, ops emails

If no klaviyo_*, resend_*, beehiiv_* or gmail_* tool is found, the integration to connect is the provider the user intends to use: Klaviyo, Resend, Beehiiv or Gmail.

How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

SurfaceFind a toolRun it
Hyper chatCall the tool by its name; search_tools(queries=["<provider> <action>"]) shows its parameters<name>(...)
MCP client (Claude, Cursor, Codex, ChatGPT)search("<what you want to do>"), then describe("<name>")call_read("<name>", {...}), call_write or call_destructive: the one that describe names in call_with
Hyper CLIhyperai search "<what you want to do>", then hyperai describe <name>hyperai call <name> --json '{...}'

If a tool is not found: in Hyper chat, find its toolkit id with discover_toolkits and pass it to enable_toolkit. On an MCP client or the CLI, tell the user which integration to connect in Hyper.

Provider selection

The wrong provider is the most common reason a lifecycle program fails. Pick first.

You are…UseWhy
An ecommerce / DTC brand on Shopify, BigCommerce, WooCommerceKlaviyoNative ecom event listeners (Placed Order, Started Checkout, Browsed Product), mature flow editor, tight Shopify sync.
A SaaS / dev tool / API product sending product + lifecycle on the same domainResendSame API for transactional + marketing, audience management, broadcasts, automation runs. Excellent deliverability for product mail.
Running a content-led newsletter (free + paid tiers)BeehiivBuilt around the newsletter-as-product model — segments, automations, paid tiers, referral program, post stats.
Running a small ops list (≤500 contacts), founder-mode broadcastsGmailZero new infra, label-based segmentation, easy templating. Don't scale beyond ~500 — see cold-email-outreach for sender deliverability if you do.

You can run more than one. The pattern is: Klaviyo for marketing, Resend for transactional + product onboarding (when the brand also runs ecom). Or Beehiiv for the newsletter and Resend for the product. Decide once per program, not per email.

Tool surface

PhaseKlaviyoResendBeehiivGmail
Audience setupklaviyo_lists_create, klaviyo_list_members_add, klaviyo_segments_create, klaviyo_profiles_create, klaviyo_profiles_updateresend_audiences_create, resend_contacts_create, resend_contacts_list, resend_contacts_updatebeehiiv_subscriptions_create, beehiiv_segments_create, beehiiv_tags_add, beehiiv_subscriptions_listgmail_labels_create, gmail_labels_add, gmail_labels_remove
Sequence buildklaviyo_campaigns_create, klaviyo_campaign_messages_updateresend_automations_create, resend_automations_update, resend_automations_getbeehiiv_posts_create, beehiiv_automations_list, beehiiv_automations_subscribers_addgmail_drafts_create, gmail_drafts_update
Send / launchklaviyo_campaigns_send, klaviyo_campaign_send_jobs_getresend_emails_send, resend_broadcasts_sendbeehiiv_posts_create (publish), beehiiv_posts_updategmail_messages_send, gmail_drafts_send
Measureklaviyo_metrics_list, klaviyo_metrics_get, klaviyo_campaigns_getresend_automation_runs_list, resend_automation_runs_getbeehiiv_posts_stats_get, beehiiv_subscriptions_getgmail_messages_list

Full per-provider mechanics, gotchas, and concrete tool-call examples in references/provider-mechanics.md.

Critical rules

  1. Pick the provider before writing copy. The mechanics of how a flow gets triggered, how a segment gets defined, and what data you can personalize against differ enough that "we'll figure out the provider later" wastes a day.
  2. Always start with the audience, not the email. A welcome flow with no opt-in source is unsendable. A win-back with no inactivity definition is unsendable. Define the audience first; the copy is downstream.
  3. One purpose per sequence. A "welcome + onboarding + product education + first purchase nudge" mega-flow is brittle and impossible to measure. Split into separate flows wired together.
  4. Honor unsubscribes globally, not per-list. When a profile unsubscribes, suppress them across every flow in the workspace — not just the one they unsubscribed from. All four providers expose this; it's not optional.
  5. Test sends with a real seed inbox before going live. Every provider supports a test send. Do not launch a 10-email sequence to a 50,000-person list without seeing every email render in Gmail / Outlook / Apple Mail / mobile.
  6. Stay under provider rate limits. Especially for resend_broadcasts_send (large blast → throttled), gmail_messages_send (~500/day soft cap), and klaviyo_campaigns_send (account-tier dependent).
  7. Track conversion metric, not opens. Apple Mail Privacy Protection makes open rates ~useless on iOS. Configure conversion events at the provider level (Klaviyo metrics, Resend automation completion, Beehiiv segment transitions) and report on those.

Workflow

Phase 1 — Define the lifecycle program

Get the user to commit to:

  1. Trigger — The event that puts a profile into this flow. Examples: "signed up for the newsletter", "made first purchase", "abandoned cart with > $50 value", "no order in 90 days".
  2. Audience filter — Beyond the trigger, who qualifies. ("Newsletter signup, but only US-based". "Abandoned cart, but only first-time visitors.")
  3. Goal — One concrete outcome the flow drives toward. Not "engage them more". Concrete: "first purchase within 14 days", "activate the integration within 7 days", "upgrade to paid within 30 days".
  4. Success metric — Conversion rate to goal. Open and click are diagnostic, not goal metrics.
  5. Suppression rules — Who should never get this flow even if they hit the trigger. (Existing customers shouldn't get the new-customer welcome. Recent purchasers shouldn't get the win-back.)

If the user can't answer the trigger or the goal, the flow isn't ready to build.

Phase 2 — Pick the sequence pattern

Five patterns cover ~95% of lifecycle work. See references/sequence-patterns.md for full templates with copy, timing, and provider-specific notes.

PatternTriggerTypical lengthGoal
Welcome / onboardingList signup3–5 emails over 7–10 daysFirst conversion (purchase, activation, paid signup)
NurtureLead magnet download, content opt-in4–7 emails over 3–6 weeksProduct-qualified action
Abandoned cart (ecom only)Started Checkout, no Placed Order2–3 emails over 24–72 hoursComplete the purchase
Re-engagementLapsed activity (e.g., no opens in 60d, no purchase in 90d)2–3 emails over 7–14 daysRe-open / re-engage
Win-backLapsed customer (no purchase in 180d+)2–3 emails over 14–21 daysRepeat purchase

Phase 3 — Build the audience

Audience setup is provider-specific. Examples for the most common case (welcome flow):

Klaviyo — create the list, then a flow trigger on "Subscribed to List":

klaviyo_lists_create(list_name="newsletter-2026")
# triggers + flows are configured in Klaviyo UI; the API surface here is
# for adding profiles, building segments, and sending one-off campaigns.

Resend — create an audience, then an automation triggered by contact.created:

resend_audiences_create(name="newsletter-2026")
resend_automations_create(
  name="welcome-2026",
  trigger="contact.created",
  audience_id="aud_...",
  ...
)

Beehiiv — subscriptions trigger automations directly when added to a segment / publication:

beehiiv_subscriptions_create(
  publication_id="pub_...",
  email="user@example.com",
  utm_source="signup-form",
)
beehiiv_automations_subscribers_add(
  automation_id="aut_...",
  subscription_id="sub_...",
)

Gmail — labels are the segment. Start with a label per program:

gmail_labels_create(name="lifecycle/welcome-2026")
# manual contact list maintained outside Gmail (Sheets, CSV) — Gmail
# is best for ≤500 contacts, founder-led sends.

Provider-specific gotchas (e.g., Klaviyo's profile-merging behavior, Resend's audience-vs-segment distinction) are in references/provider-mechanics.md.

Phase 4 — Draft the sequence

For each email in the sequence:

  1. Subject + preview text — Lifecycle subject lines should look like 1:1 mail when possible (lowercase, short). Different rules than cold email — a welcome from a brand the user just opted into can be slightly more branded.
  2. Body — One job per email. Welcome touch 1 = "thanks, here's what to expect"; touch 2 = "here's the one thing to do first"; touch 3 = "here's the proof / case study".
  3. CTA — One per email. Same rules as cold email — interest-based or single-action.
  4. Personalization tokens — Use whatever the provider exposes ({{first_name}}, {{event.product_name}}, {{custom_field.plan_tier}}). Never use a token without a fallback ({{first_name|"there"}}).

Drafts-first by default — for any new sequence, build the first email and test send it to yourself before moving on. Provider previews look correct in the editor and broken in production more often than not.

Phase 5 — Launch

  1. Test send to a seed inbox. Every provider supports it. Use it for every email before activation.
  2. Activate the flow. Klaviyo: set status to Live. Resend: enable the automation. Beehiiv: publish the post / set automation to active. Gmail: just send.
  3. Set a 7-day check-in. Most lifecycle issues (broken token, wrong audience filter, send-time-pacing surprise) show up in the first week. Pull metrics on day 7 and again on day 30.

Phase 6 — Measure & iterate

Pull the conversion to goal metric, not opens or clicks. Open rate post-MPP is noise.

ProviderConversion metric source
Klaviyoklaviyo_metrics_get(metric_id=<conversion-event>) — e.g., Placed Order attributed to the flow
Resendresend_automation_runs_list(automation_id=...) — count completed runs that hit the goal step
Beehiivbeehiiv_posts_stats_get(post_id=...) and segment-membership transitions
Gmailgmail_messages_list(query="label:lifecycle/<program> newer_than:30d") — look for replies / conversions

Iteration rule: don't tune copy until the audience is right. If the welcome flow has a 1.2% conversion and the same product organic conversion is 4%, the audience is misaligned (too broad, wrong source, suppression rules missing) — fix that first. Copy comes second.

Quality check (before launch)

Read the whole sequence end-to-end as if you're a single person receiving it over the planned timing. Reject any sequence that fails:

  • The 5-email arc tells one coherent story.
  • Each email could stand alone if the previous ones bounced.
  • Every CTA leads somewhere that still works (no broken links, no canceled offers).
  • The unsubscribe link is visible (provider auto-adds, but verify in test send).
  • Tokens have fallbacks. No Hi , after a missing first-name.
  • Subject lines are different across the sequence — same subject 5x reads as a system glitch.
  • The send time isn't 3am in the recipient's time zone.

Reference workflows

ReferenceWhen to read
references/sequence-patterns.mdBuilding a welcome / nurture / abandoned-cart / re-engagement / win-back sequence — full templates with copy, timing, and benchmarks
references/provider-mechanics.mdKlaviyo flows, Resend automations, Beehiiv segments — concrete tool-call patterns and provider-specific gotchas

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Email Lifecycle AI skill do?

Plan, build, and run lifecycle email programs through the Hyper MCP — welcome / onboarding, nurture, re-engagement, win-back, and abandoned-cart sequences across whichever provider fits (Klaviyo for ecommerce, Resend for SaaS / dev tools, Beehiiv for newsletters, Gmail for low-volume ops). Use when the user wants to build an email sequence, set up a welcome flow, recover lapsed users, send a broadcast, manage a list / audience / segment, or asks about lifecycle / drip / nurture campaigns.

Why use Email Lifecycle on TypingMind?

Because you install it once and use it with any model. Email Lifecycle is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Email Lifecycle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hyperfx-ai/marketing-skills/tree/main/skills/email-lifecycle. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Email Lifecycle?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Email Lifecycle?

As many as you like. As long as a model supports skills, you can use Email Lifecycle with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Email Lifecycle AI skill free?

Yes. It is published on GitHub by hyperfx-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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