'first-principles' 검색 결과

Axiom — First-Principles Assumption Auditor / 第一性原理拆解器 workflow skill. Use this skill when the user needs First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Axiom — First-Principles Assumption Auditor / 第一性原理拆解器 workflow skill. Use this skill when the user needs First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Use when asked for first-principles or Occam's-razor review, or when high-risk decisions involve competing constraints, fallback growth, duplicate owners, or architecture direction risk. Ordinary bug fixes stay on the fast path.

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First-principles strategy — strip away conventional assumptions and find the theoretical maximum for your business. Three modes. Diagnostic mode runs a full session (45+ min) to define your theoretical maximum, map the gap honestly, classify constraints, invert for failure modes, set strategic intent, and work backwards to your first intervention. Review mode (15-20 min) checks whether your theoretical maximum has shifted, whether the gap has changed, and whether you're still climbing the right peak. Alert mode defines constraint-shift, peak-shift, and local-peak triggers that tell you when to reassess. Use when someone is stuck optimising incrementally, when conventional wisdom is driving strategy, when a new technology or regulation changes what's physically possible, or when you suspect the business is climbing a local peak. Integrates with company-context.md. Based on practice by Eterdis (eterdis.com).

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Examine hidden assumptions behind decisions, business ideas, or personal beliefs. Classify each premise, rank it by fragility and impact, and rebuild the conclusion from verified evidence, with concrete questions showing what to check first.

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• Examining assumptions behind a career change
• Testing the premises of a startup idea
• Questioning beliefs treated as obvious facts

Generates rich technical documentation pages with dark-mode Mermaid diagrams, source code citations, and first-principles depth. Use when writing documentation, generating wiki pages, creating technical deep-dives, or documenting specific components or systems.

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Apply when integrating a new requirement into an existing design.

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Apply when integrating a new requirement into an existing design.

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When a constraint is treated as fixed, separate physics from convention, keep only independently supported primitives, and rebuild the simplest solution that satisfies real constraints.

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Deep business diagnosis for when things aren't working. Uses Socratic questioning, first-principles reasoning, and constraint analysis to find WHY a business is stuck — not just prescribe solutions. Use when the user says 'my business isn't working', 'I'm stuck', 'what's wrong', 'diagnose my business', 'why am I not growing', 'help me figure out the problem', or describes a specific business challenge.

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JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring

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MANUAL-ONLY: challenge a product idea, design, PRD, or architecture from first principles. Use only when the user names this skill. Research first, then write a local review and PRD handoff.

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Deliberate-choice procedure for a medium-to-high-stakes engineering fork — when the first plausible solution (the instinct, the default next-token pull) would be costly to get wrong. Fires AUTONOMOUSLY: invoke proactively whenever a fork fits, never wait to be asked — mechanical triggers include a fix failing for the 2nd-3rd time, adding a dependency, schema/migration design, deleting or deprecating things others depend on, changing a public API, choosing an architecture or stack. Refuse the premature collapse: hold real options open (urge · contrarian · synthesis · out-of-box · intuitive dots · precedent · first-principles), ground each branch in at least one fact from outside the model (codebase, docs, benchmark, spike), future-model consequences (blast radius, reversibility, maintenance, pre-mortem), collapse by deliberate choice, then try to refute the winner before acting. Log the decision and rejected branches in docs/decision_logs/. Not for routine calls — a decision worth more than one forward pass.

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Apply when integrating a new requirement into an existing design. Redesign as if the requirement had been a foundational assumption from day one, instead of bolting it on.

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Use this skill when reasoning about deep tech commercialization, biomedical engineering, drug delivery, material design, or overcoming institutional skepticism. Robert Langer, MIT professor and pioneer of drug delivery systems, approaches problems through first-principles engineering, interdisciplinary convergence, and relentless perseverance against consensus. Trigger this skill whenever the user is evaluating high-risk/high-reward research, deciding between incremental vs. paradigm-shifting impact, spinning out academic discoveries into startups, or designing physical/biological systems from scratch. Apply his frameworks to navigate patenting, funding, and translating lab science into real-world impact.

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This skill applies the first-principles engineering and capital allocation frameworks of Elon Musk (CEO of Tesla and SpaceX, founder of X.com / PayPal). Reach for this skill whenever the user is facing complex manufacturing bottlenecks, evaluating existential risks, debating free speech vs. censorship, dealing with bureaucratic overregulation, or trying to accelerate ambitious technical timelines. It is highly effective for situations involving hardware production, AI symbiosis, radical innovation, and aggressive execution. Use this skill proactively when discussing multi-planetary expansion, government efficiency, or scaling prototypes to mass production, even if the user doesn't explicitly name him.

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Track Serenity / @aleabitoreddit on X and turn the feed into (1) a beginner-friendly Chinese iMessage digest with first-principles + Buffett-style judgement, (2) cumulative 60-day ticker mention analytics CSVs for a website, (3) a Xiaohongshu writing brief, and (4) a durable private research map. Trigger on requests like "follow aleabitoreddit / AleaBito / Serenity", "daily Chinese updates from that X account", "60-day mention analytics", "ticker mention count", "写小红书 aleabito", "aleabito 研究地图 / research map", or any request for Chinese commentary derived from @aleabitoreddit posts.

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Apply @aleabitoreddit ("Serenity")'s distilled stock-analysis method to ANY ticker, sector, or situation — critical-chokepoint / supply-chain-OSINT idea discovery, first-principles value-chain decomposition, a Buffett-style quality gate (moat / profitability / customer-replacement risk, all default unverified), and narrative-vs-fundamentals hygiene. Produces a beginner-friendly Chinese analysis (她的观点 / 小白解释 / 第一性原理 / Buffett 直接判断 / 当前结论) that classifies an idea as 研究地图 vs 可投资结论. Trigger on "analyze like Serenity / 用 aleabito 的方法分析 / 用 Serenity 框架 / critical chokepoint 分析 / 第一性原理 + Buffett 判断这只股 / supply-chain bottleneck thesis". Never emits buy/sell calls.

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Triggers for automatically invoking the decision-framework skill before irreversible or high-blast-radius operations. Use as a checkpoint: when a proposed action matches a trigger pattern, pause and run the appropriate framework (first-principles, inversion, decision matrix, second-order thinking) before proceeding. Prevents ad-hoc calls from becoming regret.

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Derive a theoretical result step-by-step from first principles or established theorems, with every step explicitly justified and special cases checked. Use when deriving a formula or theorem from first principles, proving a mathematical statement by logical deduction, re-deriving a textbook result for verification or adaptation, extending a known result to a more general setting, or producing a self-contained derivation for a paper or thesis.

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当用户需要验证一个信念/理论/策略/商业模式的正确性、在做决策前想检验逻辑、或在问"怎么判断这个观点对不对""这个方案有没有逻辑漏洞""怎么系统地检验一个想法"时激活。 核心信号：用户需要对某个命题做系统性的逻辑验证，而非直觉判断。 不适用于：纯情感判断、不需要逻辑验证的常识性问题、时间紧迫的直觉决策。

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当用户在反思自己的认知局限、质疑群体共识、或在问"如何独立思考""怎么判断自己是不是被洗脑了""为什么我总觉得自己是对的""怎么避免从众"时激活。 核心信号：用户在做"元认知"——审视自己的思维过程本身，或在群体压力下试图保持独立判断。 不适用于：需要快速决策的紧急情况、纯技术性问题、不需要反思的信息查询。

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当用户是创业者/管理者/领导者，遇到企业增长瓶颈、转型困难、或者在问"为什么公司越大越创新不了""为什么我们总是错过新机会""公司的问题到底出在哪"时激活。 核心信号：用户在描述组织发展困境，且问题根源指向领导者自身的认知局限而非外部环境。 不适用于：非管理者的个人发展问题、纯粹的市场/竞争分析、具体业务执行问题。

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当用户面临业务增长停滞、职业瓶颈、产品创新困境，或在问"如何突破现状""怎么实现颠覆式创新""为什么总是无法超越行业领导者"时激活。 核心信号：用户在描述一个"在系统内无法解决的问题"，或试图通过优化/改善来解决本质上需要重新定义的问题。 不适用于：日常运营优化、渐进式改进、纯粹的执行力问题、信息查询。

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