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Found 1,931 Skills
Analyzes events through historical lens using source analysis, comparative history, periodization, causation, continuity/change, and contextualization frameworks. Provides insights on historical patterns, precedents, path dependency, and long-term trends. Use when: Understanding historical context, identifying precedents, analyzing change over time, comparative history. Evaluates: Causation, continuity, change, context, historical parallels, long-term patterns.
Principal backend engineering intelligence for Python AI/ML systems. Actions: plan, design, build, implement, review, fix, optimize, refactor, debug, secure, scale ML services and pipelines. Focus: data quality, reproducibility, reliability, performance, security, observability, model evaluation, MLOps.
Name a business, product, or service and secure a matching domain. Use when brainstorming names, evaluating name quality, checking domain availability, choosing between name candidates, or planning a domain strategy. Covers naming frameworks, name-quality criteria, trademark basics, domain extensions, and the full name-to-domain pipeline. Trigger on "help me name my business", "name ideas", "find a domain", "business name", "product name", "domain name", "what should I call it", "naming strategy", "check domain availability".
Comprehensive GitOps methodology and principles skill for cloud-native operations. Use when (1) Designing GitOps architecture for Kubernetes deployments, (2) Implementing declarative infrastructure with Git as single source of truth, (3) Setting up continuous deployment pipelines with ArgoCD/Flux/Kargo, (4) Establishing branching strategies and repository structures, (5) Troubleshooting drift, sync failures, or reconciliation issues, (6) Evaluating GitOps tooling decisions, (7) Teaching or explaining GitOps concepts and best practices, (8) Deploying ArgoCD on Azure Arc-enabled Kubernetes or AKS with workload identity. Covers the 4 pillars of GitOps (OpenGitOps), patterns, anti-patterns, tooling ecosystem, Azure Arc integration, and operational guidance.
Facilitates solution ideation with clear trade-offs and a final recommendation. Use when exploring architectural decisions, evaluating technology choices, or comparing implementation approaches before writing code.
Provides comprehensive guidance for learning assessment including assessment creation, evaluation methods, and assessment best practices. Use when the user asks about learning assessment, needs to create assessments, evaluate learning, or implement assessment strategies.
Runs packages temporarily, creates isolated shell environments, and evaluates Nix expressions. Use when executing tools without installing, debugging derivations, or working with nixpkgs.
Use when making high-stakes decisions under uncertainty that require stakeholder buy-in. Invoke when evaluating strategic options (build vs buy, market entry, resource allocation), quantifying tradeoffs with uncertain outcomes, justifying investments with expected value analysis, pitching recommendations to decision-makers, or creating business cases with cost-benefit estimates. Use when user mentions "should we", "ROI analysis", "make a case for", "evaluate options", "expected value", "justify decision", or needs to combine estimation, decision analysis, and persuasive communication.
Expert at analyzing documentation quality, coverage, and completeness. Auto-invokes when evaluating documentation health, checking documentation coverage, auditing existing docs, assessing documentation quality metrics, or analyzing how well code is documented. Provides frameworks for measuring documentation effectiveness.
Evaluate unit economics and capital efficiency for SaaS. Covers CAC, LTV, payback, margins, burn rate, Rule of 40, and magic number.
Technical leadership advisor for CTOs on architecture decisions, engineering strategy, team scaling, technical debt management, and technology evaluation.
Apply cognitive science and HCI research to design decisions. Use when you need the scientific 'why' behind usability, explaining user behavior, understanding perception/memory/attention limits, evaluating cognitive load, assessing mental model alignment, predicting performance with Fitts's/Hick's Law, or grounding interface decisions in research rather than opinion.