「law」の検索結果

Applies the foundationalist reasoning and methodological doubt of René Descartes (17th-century French rationalist philosopher). Use this skill whenever the user is questioning fundamental assumptions, seeking absolute certainty in a decision, dismantling flawed systems, or trying to rebuild a project from first principles. Trigger this skill for topics involving epistemology, rationalism, radical doubt, systemic reconstruction, or separating objective truth from sensory illusion. Reach for this whenever a user needs to cut through probabilities and consensus to find an indubitable 'Archimedean point' to build upon.

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Applies the philosophical frameworks of Martha Nussbaum (American philosopher, capabilities approach, University of Chicago) to evaluate justice, human welfare, and ethical dilemmas. Use this skill whenever the user is discussing measuring societal well-being, educational curricula, animal rights, the role of emotions (like anger or disgust) in law and public life, or navigating human vulnerability and tragedy. Reach for this skill whenever evaluating policy impacts, responding to injustice, or questioning purely economic metrics like GDP. It shifts the focus to what people are actually able to do and be.

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Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

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Use for local GitHub issue/PR archive search, sync freshness, clusters, durable maintainer triage, handoff to Octopool-backed gh reads, and Gitcrawl repo/release work.

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Design, review, and visually QA web and app interfaces against explicit design laws so shipped screens look intentional instead of generic AI output.

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Suede AI design skill for making an interface feel intentional instead of templated: design tokens, color strategy, OKLCH ramps, type scale, fluid type, visual hierarchy, dark mode, spacing, component laws, motion, and source-to-implementation visual QA. Use when asked to design, restyle, polish, or audit a screen; pick colors or fonts; define, fix, or document design tokens; build or repair a dark mode; review a component or a whole design system; or compare a mock, Figma frame, or reference screenshot against a rendered implementation. NOT FOR: a full design-plus-copy build, launch surface, or reference-to-target restyle (use johnny-suede-design); conversion and funnel architecture (use suede-site-alchemy); writing the words themselves (use suede-copy).

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Generate structured 8-section validation reports with verdict (GOOD/BAD/NEEDS MAJOR WORK), strengths, critical flaws, blindspots, and concrete path forward. Use after strategic-cto-mentor has completed validation analysis and needs to produce final deliverable.

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Structured legal reference for GDPR, EU AI Act, DSA/DMA, CCPA/CPRA, HIPAA (2026 updates), ADA/WCAG digital accessibility, DMCA, US state privacy laws (15+ states), and contract review.

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Objectively evaluate a UI/web design against the pols.dev anti-slop design law: detect catalogued slop tells with cited evidence, score 8 weighted axes (color, type, components, layout, motion, execution, signature, cohesion), and emit a Slop Report with a 0–100 Slop Index and grade. Use when the user asks to "evaluate design slop", "slop report", "is this design AI slop", "audit this landing page design", "de-slop review", or wants an objective score of how generic/machine-made a design looks. To fix text (not design), use human-ai or humanizar skills instead.

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用户在做资本配置决策：回购、分红、收购、再投资。关键判断"这个行动在当前价格下是聪明还是愚蠢"。 语言信号："公司要回购股票"/"应该分红还是再投资"/"这个收购价格合理吗"/"留存收益能不能创造价值" 不适用于：不涉及价格的纯经营决策。

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Create 3D models, textures, reference images, rigging and animation with Meshy, and prepare models for physical 3D printing: white or multicolor prints, Creative Lab products, sizing and slicer handoff. Drives the Meshy CLI; signs in through the browser, no API key required.

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AI knowledge engine - a memory system in 6 lines of code. remember/recall/forget/improve loop, vector + graph search, OpenClaw plugin supported.

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16 evidence-graded behavioral-economics primitives. Use when asking will this nudge work, is a pricing decoy or dark pattern lawful, or what effect size to expect.

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Sizes queues and worker pools. Use when estimating Kingman G/G/1 mean waiting time, Erlang or Little's Law sizing, p99 under load, retry storms, worker counts.

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Diagnoses stalled teams or agent hierarchies with Beer's VSM and Ashby's Law. Use when orchestrators overload, escalations pile up, or team boundaries need redesign.

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Evaluates neuromarketing studies and neural-data law. Use when judging EEG, fMRI, eye-tracking, or GSR ad study or vendor, or if signals are regulated neural data.

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Threat-models and hardens an application, API, data flow, dependency, or deployment against authentication and authorization flaws, injection, secrets exposure, unsafe deserialization, SSRF, abuse, privacy loss, and supply-chain risk. Use for security review, threat modeling, hardening, or sensitive changes. Not for generic code style review or an unexplained bug without a security hypothesis.

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Analyzing code statically for security flaws: hardcoded secrets, SQL injection, input validation, security headers, dependency CVEs. Not for runtime exploit checks (Probe) or code review (Judge).

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Design deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.

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Pre-implementation red-team analysis. Use when a plan is high-risk, critical path, or expensive to reverse. Challenges plans before code is written — finds edge cases, security holes, scalability bottlenecks, error propagation risks, and integration conflicts. Catches flaws at plan time (10x cheaper than post-implementation).

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한국 종합소득세·법인세 신고 준비를 위한 서류 체크리스트 자동 생성 스킬. 개인사업자(일반·간이·면세)·프리랜서·1인 법인·겸업·성실신고확인대상 5가지 유형별로 필요 서류 목록을 제공하고, korean-jangbu-for에서 자동 생성 가능한 항목을 표시한다. 2026년 기준 기한표(토·일 자동 이연 반영) 포함 — 종소세 일반 2026-06-01, 성실신고 2026-06-30.

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스타트업·1인 법인 대표용 경영 리포트 자동 생성 스킬. 월별 손익 추이, 현금흐름(일별 net), cash burn rate(최근 N개월 평균 순지출), 비용 구조 분석. 공식 재무제표와 별개로 의사결정용 가공 리포트 제공.

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。

한국 스타트업·1인 법인 대표·프리랜서·개인사업자를 위한 장부 자동 생성 진입점 스킬. 호출 시 5개 하위 스킬(jangbu-import·jangbu-tag·jangbu-tax·jangbu-dash·jangbu-jongso)을 번호·문자 메뉴로 제시하고, 입력 즉시 해당 스킬 인터뷰로 직행한다. 엑셀·5대 은행 CSV·7대 카드사 명세서 PDF·영수증·세금계산서 지원, macOS Vision/PaddleOCR 로컬 처리, Level 2 민감정보 마스킹.

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。

표준 거래내역에 계정과목을 매핑하는 스킬. 룰 기반 분류 우선(80%+), 실패 건만 LLM fallback(마스킹 뷰), 사용자 확인 루프. 한국 거래처 100개 시드 룰 포함, 내부 계정 ↔ 국세청 표준계정 이중 구조.

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。