agentleFS
deciqAIdeciqAI/knowledge-skills/activation-onboarding-playbook/SKILL.md

activation-onboarding-playbook

Skill13 starsChanged 4 months agoMITView on GitHub

Activate when: signups don't turn into active/paying users; 'people sign up but don't stick', designing onboarding, improving activation; aha moment, time-to-value. Do NOT activate when: the problem is acquisition (no signups) or long-term retention of already-activated users (different lever). More: deciqai.com/s/activation-onboarding-playbook

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No activation metric or funnel instrumentation.

    line 32

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Activation & Onboarding — Get to First Value Fast

Overview

Activation is the moment a new user first experiences real value — the "aha moment" — and the single biggest lever on retention and revenue for most products/services. Onboarding's job is to shrink time-to-value: get the user to that moment as fast as possible, removing every step that isn't required to feel the win.

The Process

  1. Define the aha moment — the specific action correlated with retention (e.g. "invited a teammate," "sent first invoice," "got first result"). Gate: no defined activation event = you're optimizing blind.
  2. Find the setup moment(s) — the minimum steps required to reach aha; everything else is optional.
  3. Design the shortest path — sequence only the must-do steps to first value; defer configuration.
  4. Remove/relieve friction — pre-fill, sensible defaults, do-it-for-them (concierge/agent) where possible.
  5. Nudge to the milestone — timely prompts/emails toward the aha, not generic "welcome" noise (pairs with an onboarding-sequencer).
  6. Measure activation rate and time-to-value; iterate the biggest drop-off. Gate: adding onboarding steps without measuring drop-off usually lowers activation.

When to Use

  • High signup, low activation/stick
  • New onboarding flow or high-touch service onboarding
  • Trials that don't convert to paid

Applying It Well

  • Deliver a win before asking for full setup.
  • One activation metric; instrument the funnel to it.
  • Doing the setup for the user (concierge/AI) often beats teaching them.

Red Flags

  • Long setup wizard before any value.
  • Generic welcome emails not tied to the aha.
  • No activation metric or funnel instrumentation.

Verification

  • Aha moment defined and measurable
  • Minimum path to first value mapped
  • Friction removed / setup assisted
  • Activation rate + time-to-value tracked, drop-offs iterated

Part of deciqAI Knowledge Skills — 253 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. See it run → https://www.deciqai.com/s/activation-onboarding-playbook · Built by deciqAI · github.com/deciqAI · Contributions welcome.

Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/activation-onboarding-playbook.json

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.