Ambiguous, high-value, complexity-prone 문제의 결정 품질을 개선하기위한 재사용 가능한 에이전트 기술.

이 기술은 LLM이 실제 질문을 명확하게하고, 숨겨진 가정을 노출, 근본적인 사실에서 이유, 불필요한 복잡성을 감소시키고, 더 청결한 권고 또는 다음 단계로 끝납니다.

그것은 실용적인 순서에 있는 3개의 보완적인 reasoning 형태를 결합합니다:

1.Socratic questioning는 실제 문제를 명확하게 합니다. 2. First-principles 생각 사실과 제약 문제 감소 3. **Occam-style simplification ** 불필요한 복잡성을 제거

이 스킬은

이 기술은 대리인을 돕기 위하여 디자인됩니다:

• 실제 결정 또는 질문을 식별
• 숨겨진 가정 노출
• 관성 및 컨벤션의 별도 사실
• constraints, 메커니즘 및 카우랄 구조로 문제를 감소
• 복잡성과 가정 부하에 의한 옵션 비교
• 현실을 삭제하지 않고 false complexity 제거
• 권고, 다음 이동, 또는 테스트와 끝

제일 사용 케이스

이 기술을 사용하면 다음과 같은 것들을 묻습니다.

• 나는 무엇을 누락? -이 방법을 정말 가지고 있습니까?
• 어떻게 제거해야합니까?
• 아직도 맞는 가장 간단한 설명은 무엇입니까?

decision-clarity

A reusable agent skill for improving decision quality in ambiguous, high-value, complexity-prone problems.

This skill helps an LLM clarify the real question, expose hidden assumptions, reason from fundamental facts, reduce unnecessary complexity, and end with a cleaner recommendation or next step.

It combines three complementary reasoning modes in a practical sequence:

1. Socratic questioning to clarify the real issue
2. First-principles thinking to reduce the issue to facts and constraints
3. Occam-style simplification to remove unnecessary complexity

What this skill does

This skill is designed to help agents:

• identify the real decision or question
• expose hidden assumptions
• separate facts from inertia and convention
• reduce problems into constraints, mechanisms, and causal structure
• compare options by complexity and assumption load
• remove false complexity without deleting reality
• end with a recommendation, next move, or test

Best use cases

Use this skill when the user asks things like:

• What am I missing?
• Does this really have to be this way?
• What should I remove?
• What is the simplest explanation that still fits?
• Help me think this through.
• Which option actually makes the most sense?

It is especially useful for:

• startup and business decisions
• product and MVP decisions
• content and creator workflow design
• operations and process simplification
• strategy questions with multiple plausible options
• personal decisions distorted by confusion, self-justification, or excess complexity
• argument and reasoning audits

Structure

decision-clarity/
├── SKILL.md
├── Workflows/
│   ├── Clarify.md
│   ├── Deconstruct.md
│   ├── Simplify.md
│   └── Decide.md
└── references/
    ├── anti-patterns.md
    ├── business.md
    ├── content.md
    ├── examples.md
    ├── operations.md
    ├── output-patterns.md
    ├── product.md
    └── trigger-questions.md

Workflow model

1. Clarify

Identify the real question, clean up vague framing, and expose initial assumptions.

2. Deconstruct

Reduce the problem into facts, constraints, mechanisms, and causal structure.

3. Simplify

Remove unnecessary complexity and compare options by assumption load while preserving adequacy.

4. Decide

Convert the clarified, decomposed, and simplified reasoning into a practical recommendation, next move, or test.

Included references

• anti-patterns.md — failure modes such as endless inquiry, false simplicity, and analysis without action
• business.md — startup, pricing, growth, distribution, and strategy questions
• product.md — MVP, feature decisions, onboarding, and scope simplification
• content.md — tutorials, creator workflows, and audience-value decisions
• operations.md — SOPs, approvals, handoffs, and process simplification
• trigger-questions.md — transforms vague prompts into sharper analysis frames