Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
AI founder coaching system — daily decision journal, accountability tracking, weekly strategy reviews, and AI-era specific questions on moat, commoditization...
AI founder coaching system — daily decision journal, accountability tracking, weekly strategy reviews, and AI-era specific questions on moat, commoditization...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Your AI-powered founder accountability system. A structured coaching framework for AI-era founders. Daily check-ins, decision journaling, weekly strategy reviews, and accountability tracking — all stored in your agent's memory.
# Morning check-in python3 {baseDir}/scripts/founder_checkin.py morning # Evening reflection python3 {baseDir}/scripts/founder_checkin.py evening # Weekly review python3 {baseDir}/scripts/founder_checkin.py weekly # View stats python3 {baseDir}/scripts/founder_checkin.py stats # View recent entries python3 {baseDir}/scripts/founder_checkin.py history --days 7
Use this every morning to set your day:
What did I commit to yesterday? What actually got done? (completion rate) What carried over and why?
#PriorityWhy it mattersTime block123 Rule: If you can only do ONE thing today, which is it? That's #1.
Pick one to reflect on: "What manual process am I doing that AI could handle?" "Where is my moat — data, workflow, distribution, or brand?" "What's my cost-per-serve and how do I halve it?" "Am I building a product or a feature that GPT will add next quarter?" "What would a 10-person AI-native company do differently?"
What went well today? What am I proud of?
What didn't happen? Why? What would I do differently?
Top 3 priorities for tomorrow One thing to stop doing One thing to start doing
Rate 1-5: Energy [ ] Focus [ ] Motivation [ ]
Run every Sunday or Monday. Takes 30-60 minutes.
Commitments made this week: ___ Commitments kept: ___ (___%) Trend vs last week: ↑ / → / ↓
MetricLast WeekThis WeekTargetRevenueUsers/CustomersKey Feature ProgressCost-per-serve
Moat Analysis Data moat: Are we accumulating proprietary data? What data do we have that others don't? Workflow moat: Are we embedded in customer workflows? Switching cost? Distribution moat: Do we own a channel? Community? Brand? Speed moat: Are we shipping faster than anyone else? Commoditization Risk Which parts of our stack are becoming commoditized? What happens when GPT-5 / Claude 4 / Gemini 3 drops? Are we building on top of APIs that could become competitors? AI-Era Economics Cost-per-serve: What does it cost to serve one customer? Outcome-based pricing: Can we charge for outcomes, not seats? Marginal cost: Does our 1000th customer cost the same as the 1st? AI leverage: Where does AI give us 10x leverage vs humans?
DecisionContextOptions ConsideredChosenReversible?
#1 priority (must happen): #2 priority (should happen): #3 priority (nice to have): One bet/experiment to run:
For important decisions, use this format: ## Decision: [Title] Date: YYYY-MM-DD Stakes: Low / Medium / High / Critical ### Context What's the situation? Why does this decision need to be made now? ### Options 1. **Option A:** [description] - Pro: ... - Con: ... - Cost: ... 2. **Option B:** [description] - Pro: ... - Con: ... - Cost: ... ### Decision Chose: [Option X] Reasoning: [Why] Reversible: Yes/No Review date: [When to check if this was right] ### Outcome (fill in later) Date reviewed: Result: Lesson:
Morning: Set 3 commitments Evening: Mark complete/incomplete with notes Weekly: Review completion rate and patterns Monthly: Identify systemic issues
90-100% completion: You're either crushing it or setting easy goals 70-89%: Healthy stretch zone 50-69%: Overcommitting or execution issues Below 50%: Stop. Fewer commitments. Execute on 1-2 things.
Always incomplete #3: You're overcommitting — do 2 things well Same item carrying over: It's either not important (cut it) or you're avoiding it (why?) High completion but no progress: You're busy, not productive — wrong priorities Energy always low: Burnout risk — take a break before it takes you
Rotate through these in morning briefs:
What would this business look like if AI could do 80% of the work? Are we a thin wrapper around an API? How do we add defensible value? What proprietary data or feedback loops do we create? If OpenAI built our feature tomorrow, what would still be ours?
What's our cost-per-serve and trajectory? Can we charge for outcomes instead of access? Where do margins come from when AI costs drop 10x yearly? What's our unit economics at 10x scale?
What can a 3-person AI-native startup build in 3 months that competes with us? Where do we have distribution that new entrants don't? What switching costs have we built?
Am I building a company or a project? What am I uniquely positioned to build that AI can't easily replicate? Am I spending time on $10/hr tasks or $1000/hr tasks? What would I do if I had 10x the resources? What about 1/10th?
All entries are stored in memory/founder-journal/: memory/founder-journal/ ├── 2026-02-15.md # Daily entries ├── 2026-02-16.md ├── weekly/ │ └── 2026-W07.md # Weekly reviews └── decisions/ └── 2026-02-15-decision-name.md
Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents. 📅 Need help setting up OpenClaw for your business? Book a free consultation
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
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