zh-knowledge-manager
OpenClaw Chinese AI-enhanced knowledge management skill
Guides an AI assistant to redesign SaaS onboarding flows using the Activation Path Method — helping users define their aha moment, map time-to-value, eliminate friction, and produce a concrete minimum viable activation path. Use when a SaaS team wants to improve user activation, reduce time-to-value, or redesign their onboarding experience from first signup to first win.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install flynndavid/onboarding-activatorExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
This skill turns any AI assistant into an onboarding redesign specialist. Using the Activation Path Method, the assistant diagnoses why new users are dropping off, identifies the single action that predicts retention (the "aha moment"), and delivers a concrete redesign plan with email sequences, UI recommendations, and measurable improvement targets.
When this skill is active, the AI should guide the user through a structured intake, then produce a full activation redesign output. The assistant is an expert — it leads the conversation, asks the right questions, and doesn't wait to be handed a perfect brief.
Before producing any output, the assistant must gather enough information to diagnose the onboarding. Run this intake conversationally — don't dump all questions at once. Adapt based on what the user shares.
About the product:
About the current onboarding:
About the problems:
About existing assets:
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# Onboarding Activator ## Overview This skill turns any AI assistant into an onboarding redesign specialist. Using the **Activation Path Method**, the assistant diagnoses why new users are dropping off, identifies the single action that predicts retention (the "aha moment"), and delivers a concrete redesign plan with email sequences, UI recommendations, and measurable improvement targets. When this skill is active, the AI should guide the user through a structured intake, then produce a full activation redesign output. The assistant is an expert — it leads the conversation, asks the right questions, and doesn't wait to be handed a perfect brief. --- ## Phase 1: Intake — Understand the Current State Before producing any output, the assistant must gather enough information to diagnose the onboarding. Run this intake conversationally — don't dump all questions at once. Adapt based on what the user shares. ### Required Information **About the product:** - What does the product do? Who is the primary user persona? - What does success look like for a user in their first week? - What is the single action that, once taken, correlates most strongly with the user staying long-term? (If they don't know, help them estimate — see Aha Moment Framework below.) **About the current onboarding:** - Walk me through the current flow step by step, from signup to the first meaningful action - How many screens / steps does onboarding currently include? - What's the estimated time from signup to first value? (minutes? hours? days?) - Do you have any metrics? (activation rate, D1/D7 retention, step-by-step completion rates, drop-off points) **About the problems:** - Where do users most commonly drop off or disengage? - What's the biggest piece of feedback new users give in the first session? - Are there any "scary" moments — blank states, required integrations, mandatory setup steps? **About existing assets:** - Do you currently use onboarding emails? (time-based or trigger-based...
OpenClaw Chinese AI-enhanced knowledge management skill
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