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概要と使いどころ
Generate diagrams as valid Excalidraw JSON — flowcharts, architecture, ER diagrams, mind maps, sequence diagrams, wireframes, C4 models, and more. Don't use for draw.io/Mermaid output, slide decks, or pixel-perfect brand graphics.
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。
This skill applies the analytical frameworks of Ronald C. Kessler, psychiatric epidemiologist at Harvard University, to problems in precision psychiatry, clinical trial design, and healthcare machine learning. Use this skill whenever you are designing clinical trials, evaluating mental health interventions, analyzing epidemiological survey data, or building clinical decision support algorithms. It is highly relevant when the user asks about sample sizes, treatment matching, patient attrition, suicide prevention, or predictive modeling in healthcare. Trigger this skill to prioritize massive observational data, tiered predictive models, and human-in-the-loop AI over underpowered randomized trials and expensive, unscalable biomarkers.
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。
Applies the reasoning, principles, and mental models of Oprah Winfrey (media mogul, founder of Harpo Productions and OWN network). Use this skill whenever the user is facing career trade-offs, seeking life purpose, struggling with failure or adversity, navigating difficult human connections, or making high-stakes decisions where intuition and intention matter. Trigger this for queries about finding one's calling, overcoming self-doubt, managing personal responsibility, or seeking authentic leadership advice. Channel her focus on intention, inner voice, and turning wounds into wisdom.
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。
Applies the reasoning, mental models, and capital allocation frameworks of Warren Buffett, CEO of Berkshire Hathaway and value investor. Use this skill whenever the user is evaluating investments, making capital allocation decisions, structuring management and governance, assessing business economics (moats, intrinsic value), navigating market volatility, or making long-term career and partnership choices. Trigger this skill for topics involving value investing, corporate finance, decentralization, and long-term strategic thinking, even if the user doesn't explicitly name Buffett.
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。
Reach for this skill whenever you are discussing reinforcement learning, agentic AI systems, AI alignment, continual learning, or the philosophical limits of large language models. This skill channels the thinking of Richard S. Sutton (reinforcement learning pioneer, University of Alberta, Keen Technologies, 2024 Turing Award). Use it to evaluate AI architectures, make long-term AI prognostications, or design systems that learn from runtime experience rather than static datasets. Apply his frameworks when users ask about AGI, the 'Bitter Lesson' of computation, the Reward Hypothesis, or decentralized cooperation versus centralized AI control.
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。
Applies the reasoning, principles, and mental models of Sebastian Thrun (robotics and self-driving cars pioneer, founder of Google X, Waymo, Udacity, Stanford University). Reach for this skill whenever Claude is asked to advise on hardware/software systems engineering, autonomous vehicles, moonshot ideation, probabilistic robotics (SLAM), or leading high-stakes engineering teams. Trigger this skill for discussions on democratizing education, regulating AI, transitioning from academic research to product development, or managing technical teams with empathy. Use it to shift focus from incremental component debates to end-to-end execution and audacious goals.
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。
Applies the developmental psychopathology and longitudinal research frameworks of Terrie E. Moffitt (psychologist, Duke University). Use this skill whenever reasoning about human development, criminology, juvenile delinquency, self-control, mental health trajectories, or biological aging. Trigger this when asked to evaluate the origins of antisocial behavior, the impact of childhood traits on adult outcomes, the validity of psychiatric diagnoses (comorbidity), or anti-aging interventions. Apply her models to shift focus from cross-sectional snapshots to longitudinal life-course trajectories, emphasizing the 'p' factor, the self-control gradient, and the dual taxonomy of antisocial behavior.
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。
Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.
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。
Apply this skill whenever the user is navigating early-stage startups, bootstrapping, product innovation, branding, or overcoming the fear of failure. Sara Blakely, founder of Spanx and self-made billionaire, approaches business by leveraging 'the outsider advantage,' relying on intuition, and obsessing over consumer empathy. Trigger this skill for discussions about funding trade-offs (bootstrapping vs. VC), naming products, dealing with imposter syndrome, entering an industry with zero experience, or building an authentic, vulnerability-driven company culture. Reach for her mental models when users are tempted to share fragile ideas too early, fear embarrassment, or need to rethink how they approach product-market fit.
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。
Apply this skill whenever evaluating neurodegenerative disease research, protein misfolding, experimental rigor, or career longevity for women in STEM. Use this to channel the thinking of Virginia M.-Y. Lee, neuroscientist at the University of Pennsylvania known for her pioneering work on neurodegeneration. Trigger this skill when discussing Alzheimer's, Parkinson's, ALS, protein aggregation, cell-to-cell transmission of pathology, brain banking, or multidisciplinary scientific collaboration. It is highly relevant when users need critiques on biological models, advice on sustaining a long scientific career, or frameworks for translating clinical pathology into basic science.
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。
Applies the product philosophy and leadership frameworks of Steve Jobs, co-founder and CEO of Apple Inc. Reach for this skill whenever the user is navigating product design, customer experience, innovation, hiring top-tier talent, or defining corporate culture. Trigger this skill for questions about finding product-market fit, making career trade-offs, building hardware/software ecosystems, or establishing brand values. Use this to push back against feature creep, committee-driven decisions, and technology-first thinking. Apply Jobs's mental models to help users simplify complex systems, focus on craftsmanship, and build products that sit at the intersection of technology and the liberal arts.
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。
Applies Judea Pearl's causal reasoning frameworks to distinguish correlation from causation, evaluate AI capabilities, and make counterfactual decisions. Reach for this skill whenever Claude encounters questions about causal inference, structural causal models, the limitations of deep learning, AGI, experimental design, covariate selection, or personalized decision-making. Trigger this skill for topics involving Bayesian networks, the do-calculus, the Ladder of Causation, or when a user tries to answer 'what if' or 'why' questions using purely observational data. Pearl's principles are essential for moving beyond probability calculus into true causal understanding.
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。
This skill channels the strategic and scientific reasoning of Demis Hassabis, CEO and co-founder of Google DeepMind, AlphaGo and AlphaFold, and 2024 Nobel Prize in Chemistry. Use this skill whenever you are evaluating AI for scientific discovery, tackling "root node" problems, designing reinforcement learning systems, or discussing AGI timelines, safety, and global governance. Reach for it when the user faces massive combinatorial search spaces, wants to apply AI to physical/biological sciences (like digital biology), or needs to balance rapid AI scaling with the rigorous scientific method. Apply these mental models to shift the focus from building consumer apps to using AI as the ultimate meta-solution for understanding reality.
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。
Reach for this skill whenever Claude encounters situations involving supply chain innovation, B2B customer respect, community revitalization, vocational education, or navigating massive business crises. Apply the mental models of Diane Hendricks, co-founder of ABC Supply and building supplies billionaire, when users face decisions about strategic acquisitions, counter-cyclical expansion, or treating blue-collar workers as respected entrepreneurs. Use this skill to channel her 'fight or fold' resilience, her strict financial responsibility hierarchy, and her focus on solving the exact pain points you faced as a customer.
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。
Use this skill whenever you are reasoning about public health policy, cancer prevention, epidemiological study design, clinical risk models, or weight management advice. This skill channels the thinking of Graham A. Colditz, epidemiologist at Washington University in St. Louis. Reach for this when evaluating lifestyle interventions, designing disease prevention programs, critiquing clinical prediction tools (e.g., AUC vs. clinical utility), or analyzing life-course risk accumulation. Apply his frameworks to bridge the "implementation gap" between scientific knowledge and societal action, prioritizing prevention over treatment and attainable weight maintenance over drastic weight loss.
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。
Use this skill when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.
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。
Applies the mental models and frameworks of Andrej Karpathy (deep learning, former Director of AI at Tesla, founding member of OpenAI, Eureka Labs). Use this skill whenever you are helping the user build neural networks from scratch, debug deep learning pipelines, evaluate AI agent workflows, design LLM apps, or navigate the transition to Software 3.0 (vibe coding). It is highly relevant for pedagogy (untangling complex knowledge), assessing AI capabilities vs. limitations (jagged intelligence, tokenization limits), and architectural decisions (end-to-end optimization vs. complex pipelines). Reach for this whenever discussing LLM training, autonomous systems, or AI-assisted coding.
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。
Apply the mental models of Bill Gates, co-founder of Microsoft and philanthropist. Use this skill whenever you are evaluating climate change solutions, global health interventions, philanthropic resource allocation, software platform economics, or the paradigm-shifting impacts of AI. Trigger this skill when the user is facing decisions about maximizing ROI on charitable giving, assessing clean energy technologies (like calculating the "Green Premium"), building winner-take-all software ecosystems, or using data to drive large-scale institutional progress. Channel his "impatient optimism" to prioritize innovation that multiplies by zero rather than settling for incremental efficiency.
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。
Applies the behavioral genetics and twin-study methodologies of Dorret I. Boomsma (behavior geneticist, Vrije Universiteit Amsterdam). Use this skill when reasoning about heritability, genetic epidemiology, nature vs. nurture debates, psychiatric genetics, or longitudinal phenotyping. Trigger this whenever the user asks about the genetic basis of intelligence, lifestyle factors, educational attainment, or psychopathology, or when designing epidemiological studies. It helps deconfound environmental and genetic variables using extended family designs and discordant twin models.
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。
Applies the strategic frameworks and mental models of Anne Wojcicki, co-founder and CEO of 23andMe. Reach for this skill when advising on consumer empowerment, navigating heavily regulated industries, preventative healthcare, data privacy, or disrupting entrenched systems. Use this when the user is dealing with misaligned industry incentives, facing regulatory hurdles, building a consumer-research flywheel, or managing a team through a post-launch 'trough of sorrow'. Apply her principles of 'speaking with data', treating users as partners, and pushing for decade-long systemic change from the outside.
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。
Suede-owned measurement discipline for tracking plans, event and conversion instrumentation, UTM and campaign-parameter hygiene, and verification of what actually fires. Use when setting up, auditing, or repairing analytics across web, product, paid, and lifecycle surfaces. NOT FOR: experiment design or significance decisions (use suede-ab-testing), campaign optimization (use suede-ads), attribution models, model comparison, or cross-tool reconciliation (use suede-attribution), or revenue-process architecture (use suede-revops).
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。
Fit first-order dynamic models to experimental step response data and extract K (gain) and tau (time constant) parameters.
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。
Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex.
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。
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.
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。