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Structured hypothesis formulation: turn observations into testable hypotheses with predictions, propose mechanisms, design experiments. Follows the scientific method. Use scientific-brainstorming for open ideation; hypogenic for automated LLM hypothesis testing on datasets.
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Provides Gemini CLI delegation workflows for large-context analysis and complex reasoning using Gemini 3.0 Flash and Gemini 3.0 Pro models, including English prompt formulation, execution flags, and safe result handling. Use when the user explicitly asks to use Gemini for tasks such as broad codebase analysis, fast iterations with Gemini 3 Flash, or deep architectural reasoning with Gemini 3 Pro. Triggers on "use gemini", "delegate to gemini", "run gemini cli", "ask gemini", "use gemini for this task", "use gemini 3 flash", "use gemini 3 pro".
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Provides Qwen Coder CLI delegation workflows for coding tasks using Qwen2.5-Coder and QwQ models, including English prompt formulation, execution flags, and safe result handling. Use when the user explicitly asks to use Qwen for tasks such as code generation, refactoring, debugging, or architectural analysis. Triggers on "use qwen", "use qwen coder", "delegate to qwen", "ask qwen", "second opinion from qwen", "qwen opinion", "continue with qwen", "qwen session".
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Provides Codex CLI delegation workflows for complex code generation and development tasks using OpenAI's GPT-5.3-codex models, including English prompt formulation, execution flags, sandbox modes, and safe result handling. Use when the user explicitly asks to use Codex for complex programming tasks such as code generation, refactoring, or architectural analysis. Triggers on "use codex", "delegate to codex", "run codex cli", "ask codex", "codex exec", "codex review".
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Guides privacy audit report writing including executive summary drafting, findings classification (critical, high, medium, low), evidence referencing, root cause analysis documentation, recommendation formulation, management response tracking, and report distribution protocols. Covers report structure from scope definition through appendices and sign-off. Keywords: audit report, findings documentation, executive summary, recommendations, report structure, privacy audit deliverables.
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Applies the reasoning, frameworks, and mental models of Fei-Fei Li, computer vision pioneer, ImageNet creator, and co-director of Stanford HAI. Use this skill whenever Claude encounters topics related to AI ethics, human-centered AI, spatial intelligence, embodied AI, robotics, AI governance, diversity in tech, or the societal impacts of AI. Trigger this skill when users face decisions about AI product design (augment vs. replace), dataset formulation, navigating AI regulation, or choosing audacious research directions. Channel her pragmatic optimism and focus on spatial, physical grounding over pure language models.
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Think and work like an expert Mathematical Modeler. Use when a task calls for Mathematical Modeler judgment. Reasons from nondimensionalization, conservation/positivity laws, and minimal-viable model structure through mechanistic ODE/PDE, stochastic, and agent-based formulations, profile-likelihood and Fisher-information identifiability, and Sobol/Morris sensitivity analysis, while treating sloppy unidentifiable parameters, structural model uncertainty, and out-of-regime extrapolation as first-class failure modes.
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Think and work like an expert Dairy Scientist. Use when a task calls for Dairy Scientist judgment. Reasons from the lactation curve, dry matter intake, and rumen health through NASEM Dairy 2021/CNCPS ration formulation, Penn State particle separation, DHIA records, and pen-level mixed models while treating subacute ruminal acidosis, milk fat depression, transition-cow hypocalcemia, and unadjusted DIM/parity confounding as first-class failure modes.
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Think and work like an expert Applied Mathematician. Use when a task calls for Applied Mathematician judgment. Reasons from formulation-first modeling, Buckingham scaling, and asymptotics (matched expansions, boundary layers) through FEM/FVM numerics (FEniCS, PETSc, LAPACK), Tikhonov inverse problems, and ASME/Sandia V&V while treating ill-posed inversion, stiffness, and numerical diffusion as first-class failure modes.
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Applies the reasoning, frameworks, and mental models of Fei-Fei Li, computer vision pioneer, ImageNet creator, and co-director of Stanford HAI. Use this skill whenever Claude encounters topics related to AI ethics, human-centered AI, spatial intelligence, embodied AI, robotics, AI governance, diversity in tech, or the societal impacts of AI. Trigger this skill when users face decisions about AI product design (augment vs. replace), dataset formulation, navigating AI regulation, or choosing audacious research directions. Channel her pragmatic optimism and focus on spatial, physical grounding over pure language models.
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Regression analysis, ANOVA, generalized linear models, Bayesian methods, and model selection. Covers the full modeling workflow from problem formulation through diagnostics -- linear regression, logistic regression, Poisson regression, mixed-effects models, prior specification, posterior inference, AIC/BIC comparison, cross-validation for model selection, and assumption checking. Use when fitting models, testing hypotheses, or selecting among competing statistical explanations.
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A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from data.
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Use when facing unknowns, debugging without a clear cause, or making architecture decisions — enforces hypothesis-driven scientific reasoning through observation, hypothesis formulation, prediction, experiment design, and evidence-based conclusion. Use when previous attempts have failed or the problem space involves uncertainty.
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Formulate a quantum mechanics or quantum chemistry problem with proper mathematical framework including Hilbert space, operators, boundary conditions, and approximation method selection. Use when setting up a quantum mechanics problem for analytic or numerical solution, formulating a quantum chemistry calculation, translating a physical scenario into the Schrodinger or Dirac formalism, or choosing between perturbation theory, variational methods, DFT, and exact diagonalization.
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Apply WIT (Writing Is Thinking) as a human–LLM collaborative scientific reasoning skill for scientific question formulation, finding-driven research planning, next-experiment selection, Results or Discussion review, claim–evidence and reviewer stress tests, manuscript logic audits, deadline closure, and researcher growth. Use when the user invokes WIT or asks for these question-driven scientific reasoning workflows; do not use for generic copyediting, summarization, or literature search alone.
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Use this skill when writing sprint contracts in VCSDD strict mode. Provides grading criteria patterns, dimension weight guidelines, and pass threshold formulation for the 5 review dimensions.
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Condense long reports, documents, or data exports into structured summaries with key findings, implications, and recommended actions. Use when the work is distilling dense content for busy readers. Do not use for original analysis, strategy formulation, or when the source material needs expert interpretation beyond summarization.
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Fierce autonomous internal co-founder. Bounded web research for evidence-backed improvements. Structured idea formulation with self-critique filter that rejects ideas not serving the goal. Auto-implements high-confidence aligned improvements, proposes medium-confidence ideas for approval. Evaluates viral coefficient, AI search visibility (GEO), and solo SaaS economics. Considers higher pursuits: employing disabled people, spiritual tech investigation, 99% wealth donation ethos.
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Use when a task needs the judgment of a doctoral-level Clinical or Counseling Psychologist — building a psychological test battery to answer a referral question, interpreting a WAIS/MMPI/PAI profile against validity indices, working a differential diagnosis (e.g. ADHD vs. anxiety-driven inattention, depression vs. early dementia), or writing a feedback-session-ready diagnostic formulation report.
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Mandatory 3-phase explore-reason-act workflow before code modification. Enforces read-before-write, root cause hypothesis formulation, minimal change application. Triggered by "explore" ("탐색"), "reason" ("추론"), "read before write", "root cause" ("근본 원인") keywords.
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Suggests using hydrocortisone 15–25 mg or cortisone acetate 20–35 mg daily in two or three divided oral doses for adult primary adrenal insufficiency (PAI) patients initiating glucocorticoid replacement. The highest dose is given upon awakening, with the second dose either early afternoon (≈2 h after lunch) or split into lunch and afternoon doses; consider total daily dose calculation based on chosen formulation and frequency.
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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
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Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
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