EKB Decision System Skill
EKB Decision System Skill
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Description
Use probabilistic thinking and mathematical tools to help you scientifically analyze major decisions, calculating "whether to do it", "how much to invest", and "how to continuously optimize".
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High-Value Decision Advisor
When you are grappling with 'whether to do something', 'whether to choose a certain option', 'whether it's worth investing resources', or want to review 'why that decision turned out the way it did', this Skill acts like a warm project evaluation advisor, helping you break down vague thoughts into assessable evidence. It is suitable for: - Career choices: whether to change jobs, switch careers, join a startup, pursue graduate studies; - Education and growth investments: whether to enroll children in classes, buy courses, commit to a long-term learning plan; - Project and opportunity evaluation: whether to start a project, take on a partnership, invest resources; - Relationships and life choices: whether to confess feelings, move, change living arrangements; - Historical decision review: review a resignation, postgraduate exam, investment, partnership, or relationship choice. It automatically adjusts the depth of reasoning based on the decision magnitude: - Lightweight decisions: quickly clarify key variables and give brief advice; - Medium-weight decisions: structured analysis around necessity, feasibility, risk, timing, and alternatives; - Heavyweight decisions: full project-style reasoning, outputting risk warnings, directional recommendation, and action paths; - Review-type questions: helps you reconstruct the judgment chain at that time, identify prediction biases and transferable lessons. You can start like this: - 'Should I sign my child up for a 20,000 per year English class?' - 'Should I leave my stable job for a startup?' - 'I want to review my decision last year to resign and study for graduate exams.' - 'I'm not sure whether to confess my feelings, can you help me analyze it?' - 'Is this opportunity worth my time and money?' In the end you will get: - A clear directional recommendation: recommend to proceed / recommend to hold off / recommend to gather more information before deciding; - The confidence level and key uncertainties for each recommendation; - The risks you most easily overlook; - The next minimal validation step. Note: It will not pretend to be certain with insufficient information and make decisions for you; it will help you see the decision basis, risk boundaries, and what to verify next.
Stock Picking Decision Engine
Every investor has experienced these moments: • 📝 Impulse buying that ends in regret — you see a stock rise for three days, your hand itches, you place an order, and end up buying at the top. • 🤔 Deciding without enough research — you read one analysis article and think you 'get it,' but you can't even explain how the company makes money. • 💸 Not knowing when to sell — you won't sell when you're winning, you can't accept selling at a loss, and in the end you get hurt on both sides. • 🎭 Being swept up by market sentiment — you panic when others panic, get greedy when others get greedy, and forever chase rallies and dump stocks on declines. • 🔄 Repeating the same mistakes — with no review system, every trade starts from scratch. The investment decision system was created to solve these problems. It is not a tool that helps you find reasons to buy; it is a decision brake system that helps you identify the moments when you 'shouldn't buy.' There is only one core principle: a good company ≠ a good stock.
How to Choose
Turn any difficult choice into a decision card: automatically fill in overlooked hidden options, anchor with probability ranges, first check for ruin risk then calculate the value bet ratio, find the linchpin assumption that if changed would flip the outcome, offer reversible hedging advice, and include an independent body signal check. Analysis depth automatically scales with bet size, helping you see whether this bet is worth taking and how to take it.
Information
- Version
- v1
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
