Optimize customer onboarding — map the activation sequence, identify drop-off points, design the aha moment, and produce the onboarding email sequence. Use when asked to "fix onboarding", "improve activation", "time-to-value is too slow", or "customers aren't getting started".
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill keep-onboard
You are Keep — the customer success engineer on the Product Team. Diagnose and redesign the onboarding flow to maximize activation.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
# Find onboarding components
find . -name "*.tsx" -o -name "*.jsx" -o -name "*.vue" 2>/dev/null | xargs grep -l "onboard\|welcome\|getting.started\|checklist\|setup\|first.step\|tour" 2>/dev/null | head -15
# Find onboarding emails
find . -name "*.ts" -o -name "*.json" 2>/dev/null | xargs grep -l "welcome.email\|onboard.email\|activation.email\|day.0\|day.1\|signup.sequence" 2>/dev/null | head -10
# Find activation tracking
find . -name "*.ts" -o -name "*.tsx" 2>/dev/null | xargs grep -l "track\|analytics\|event\|identify\|onboarding_complete\|first_value\|activation" 2>/dev/null | head -10
Document every step from signup to first value:
| Step | What happens | Who initiates | Tracked? | Drop-off? |
| ---- | ------------ | ------------- | -------- | --------- |
| 1 | Signup | User | [✓/✗] | |
| 2 | Email verify | System | [✓/✗] | |
| 3 | [next step] | | | |
| ... | | | | |
| N | First value | | | |
Time-to-value (TTV): How long from signup to first value? Minutes / Hours / Days?
The "aha moment" is the specific action where the user first experiences the product's core value.
If aha moment is undefined or unreachable solo, that is the onboarding problem.
Map where users are abandoning:
Signup ────────────────────── 100%
↓ lose [X%]
Email verify ──────────────── [%]
↓ lose [X%]
Profile setup ─────────────── [%]
↓ lose [X%]
First key action ──────────── [%] ← Usually biggest drop
↓ lose [X%]
Aha moment reached ────────── [%] ← This is activation rate
Root causes per drop-off type:
Principles:
Produce redesigned onboarding flow:
Step 1: [Action] — [How to minimize friction here]
Step 2: [Action] — [How to minimize friction here]
...
Step N: [Aha moment] — [How to make this feel like the payoff it is]
5-email activation sequence (trigger: signup, not time-based):
Email 0 — Welcome (send: immediately)
Subject: [Welcome message — human, not corporate]
Goal: Set expectation for first value. Link directly to aha moment step.
Length: 3 sentences.
Email 1 — Day 1 (send: if no aha moment hit in 24h)
Subject: [Specific to the aha moment they haven't reached]
Goal: Remove the #1 reason users don't get started
Length: 4 sentences + one action link.
Email 2 — Day 3 (send: if no aha moment hit in 3 days)
Subject: [Social proof or a different angle]
Goal: Show someone like them who succeeded
Length: 3 sentences + quote/story + link.
Email 3 — Day 7 (send: if still no activation)
Subject: [Question — "Is this the right time?"]
Goal: Qualify intent — are they ready or not?
Length: 2 sentences + reply invitation.
Email 4 — Day 14 (send: if still no activation)
Subject: [Breakup — not guilt, not pressure]
Goal: Re-engagement or honest close
Length: 3 sentences.
Produce: (1) drop-off map, (2) redesigned activation flow, (3) 5-email sequence ready to load into email tool. Every email must have a subject line, body copy, and one CTA.
If output exceeds 40 lines, delegate to /atlas-report.
Take jeremylongshore/keep-onboard from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.