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first-principles-thinking

Use for first principles thinking, or when the user questions an inherited default: "why do we do it this way?", "is this cost really necessary?", "should we copy what competitors do?". Strips analogies and rebuilds from fundamentals. Skip for convention-following checklists.

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  • references/example.md1.8 KB

SKILL.md(原文)

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First Principles Thinking

Question inherited baggage. Rebuild only from bedrock you can defend.

When to use

  • "Why do we do it this way?", "is this really required?", "what would this cost if we started from scratch?"
  • A strategy or design copied from an incumbent ("like Uber for X") that nobody has checked.
  • Cost, architecture or process choices that exist only because they always have.

Skip: quick convention-following checklists with no wish to revisit assumptions, or purely social coordination with nothing to model.

Before you start

  1. State in one block: Reconstruction target (belief, cost, design or strategy to ground) and Pass (Surface, Question, Bedrock, Rebuild, Implications).
  2. Gather first. Read the code, contracts, specs or data that show what is actually required (a regulation, an SLA, a measured limit) before tagging anything fundamental. Ask up to 3 questions only for immutable constraints that tools cannot answer.
  3. Light path. Small ask: 3 assumptions, 3 bedrock items, a 3-step rebuild, 2 implications.

Steps

1. Surface

State the conventional answer or the analogy people rely on. List loaded words and hidden comparisons.

2. Question

For each major assumption: Assumption: ... - Why believed? (authority, analogy, experience) - What if false?

3. Bedrock

List truths that survive scrutiny: physics, logic, arithmetic, legal musts, documented needs of real users. Tag each [FUNDAMENTAL] or [ASSUMPTION].

Aim for three or more honest bedrock items. If fewer exist, say why in one line.

4. Rebuild

Derive conclusions in numbered steps using only [FUNDAMENTAL] items. "Industry standard" is not a premise unless translated into a fundamental (for example "buyers require SLA X because regulation Y"). A new premise goes into Bedrock first, with a tag.

5. Implications

  • So what: what changes versus the conventional path.
  • Cost of being wrong if a tagged assumption fails.
  • A short vs convention contrast when it helps the decision.

If bedrock is too thin to rebuild, write insufficient grounding and list the evidence that would fix it.

Pitfalls

  • Calling a preference or a habit "fundamental".
  • Rebuilding from first principles and arriving exactly at the old answer. That is fine if each step is defended; say so.
  • Faux profundity. Keep every step short and checkable.
  • Ignoring switching cost. A better design from scratch may not beat the current one after migration.

Worked example: references/example.md.

Checklist

  • Target and Pass stated
  • Surface names the convention or analogy
  • Question ties each assumption to why it is held
  • Bedrock tagged [FUNDAMENTAL] or [ASSUMPTION]
  • Rebuild uses only fundamentals
  • Implications name what changes and the cost of being wrong

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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概要と使いどころ

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日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

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日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

Use for critical thinking, or when the user wants a claim, plan or decision checked for weak spots: "is this right?", "what am I missing?", "poke holes", "sanity check", "devil's advocate", "red team this". Skip for execution-only tasks and wording edits.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

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日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

Use for ethical thinking, or when a plan could harm or unfairly burden people: "should we do this?", "is this fair?", "privacy or bias risk", "who gets hurt?". Maps stakeholders, harms, power and consent. Skip for legal advice, neutral fact lookups and implementation-only work.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

Use for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even feasible?". Decomposes, uses ranges and sanity-checks. Skip when exact data is available or a precise calculation is wanted.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills112026年10月8日 更新

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