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Keep Onboard Agent Skill

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".

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2679
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill keep-onboard

What it tells the agent to use

found in the instruction text
WebFetch fetches pages from the network

The instruction itself

9 sections, as written by the author

Onboarding Optimization

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.

Steps

Step 0: Scan Existing Onboarding

# 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

Step 1: Map Current Activation Sequence

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?

Step 2: Define the Aha Moment

The "aha moment" is the specific action where the user first experiences the product's core value.

  • What is the aha moment for this product? (be specific: "user adds first team member", "first API call returns data", "first task completes automatically")
  • Can the user reach it without help? (test this: sign up as a new user and try)
  • Is it tracked? (event name?)
  • % of users who reach it within 7 days? (target: 40%+)

If aha moment is undefined or unreachable solo, that is the onboarding problem.

Step 3: Identify Drop-Off Points

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:

  • Drop at email verify: friction, users don't trust the product yet
  • Drop at profile setup: too many required fields, unclear value
  • Drop at first action: UX unclear, missing data/context, value not obvious
  • Drop before aha: too many steps before the payoff

Step 4: Design Optimized Onboarding

Principles:

  • Aha moment as fast as possible. Every step before it is friction to minimize.
  • Show value before asking for information. Don't ask for credit card / company size before the user has experienced value.
  • Progress indicators reduce anxiety. Users who don't know how long setup takes abandon faster.
  • Empty state is a call to action. Don't show an empty dashboard — show the first action to take.

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]

Step 5: Write Onboarding Email Sequence

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.

Delivery

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.

How to use it

Copy the folder

Take jeremylongshore/keep-onboard from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.