aka. Agent Skills
Discover skills for AI coding agents. Works with Claude Code, OpenAI Codex, Gemini CLI, Cursor, and more.
Use when managing project uncertainty through structured risk tracking, identifying and assessing risks with probability×impact scoring (risk matrix), assigning risk owners and mitigation plans, tracking contingencies and triggers, monitoring risk evolution over project lifecycle, or when user mentions risk register, risk assessment, risk management, risk mitigation, probability-impact matrix, or asks "what could go wrong with this project?".
Use when ranking backlogs, deciding what to do first based on effort vs impact (quick wins vs big bets), prioritizing feature roadmaps, triaging bugs or technical debt, allocating resources across initiatives, identifying low-hanging fruit, evaluating strategic options with 2x2 matrix, or when user mentions prioritization, quick wins, effort-impact matrix, high-impact low-effort, big bets, or asks "what should we do first?".
Use when analyzing failures, outages, incidents, or negative outcomes, conducting blameless postmortems, documenting root causes with 5 Whys or fishbone diagrams, identifying corrective actions with owners and timelines, learning from near-misses, establishing prevention strategies, or when user mentions postmortem, incident review, failure analysis, RCA, lessons learned, or after-action review.
Use when managing multiple initiatives across time horizons (now/next/later, H1/H2/H3), balancing risk vs return across portfolio, sizing and sequencing bets with dependencies, setting exit/scale criteria for experiments, allocating resources across innovation types (core/adjacent/transformational), or when user mentions portfolio planning, roadmap horizons, betting framework, initiative prioritization, innovation portfolio, or resource allocation across horizons.
Use when reviewing any scientific document for logical clarity, argument soundness, and scientific rigor. Invoke when user mentions check clarity, review logic, scientific soundness, hypothesis-data alignment, claims vs evidence, or needs a cross-cutting scientific logic review independent of document type.
Use when writing or polishing professional scientific emails, journal cover letters, or responses to reviewers. Invoke when user mentions email to collaborator, cover letter to editor, reviewer response, professional correspondence, or needs help with professional tone, clear asks, or diplomatic communication in academic/scientific contexts.
Use when clarifying fuzzy boundaries, defining quality criteria, teaching by counterexample, preventing common mistakes, setting design guardrails, disambiguating similar concepts, refining requirements through anti-patterns, creating clear decision criteria, or when user mentions near-miss examples, anti-goals, what not to do, negative examples, counterexamples, or boundary clarification.
Use when need systematic innovation through comprehensive solution space exploration, resolving technical contradictions (speed vs precision, strength vs weight, cost vs quality), generating novel product configurations, exploring all feasible design alternatives before prototyping, finding inventive solutions to engineering problems, identifying patent opportunities through parameter combinations, or when user mentions morphological analysis, Zwicky box, TRIZ, inventive principles, technical contradictions, systematic innovation, or design space exploration.
Use when you have implemented an equivariant model and need to verify it correctly respects the intended symmetries. Invoke when user mentions testing model equivariance, debugging symmetry bugs, verifying implementation correctness, checking if model is actually equivariant, or diagnosing why equivariant model isn't working. Provides verification tests and debugging guidance.
Use when setting product North Star metrics, decomposing high-level business metrics into actionable sub-metrics and leading indicators, mapping strategy to measurable outcomes, identifying which metrics to move through experimentation, understanding causal relationships between metrics (leading vs lagging), prioritizing metric improvement opportunities, or when user mentions metric tree, metric decomposition, North Star metric, leading indicators, KPI breakdown, metric drivers, or how metrics connect.
Use when complex systems need visual documentation, mapping component relationships and dependencies, creating hierarchies or taxonomies, documenting process flows or decision trees, understanding system architectures, visualizing data lineage or knowledge structures, planning information architecture, or when user mentions concept maps, system diagrams, dependency mapping, relationship visualization, or architecture blueprints.
Use when reasoning across multiple abstraction levels (strategic/tactical/operational), designing systems with hierarchical layers, explaining concepts at different depths, maintaining consistency between high-level principles and concrete implementation, or when users mention 30,000-foot view, layered thinking, abstraction levels, top-down design, or need to move fluidly between strategy and execution.
Use when writing or reviewing career documents including research statements, teaching statements, diversity statements, CVs, or biosketches. Invoke when user mentions research statement, teaching philosophy, diversity statement, biosketch, academic CV, faculty application, or needs help with career narrative, positioning, or professional documents for academic advancement.
Use when teams need shared direction and decision-making alignment. Invoke when starting new teams, scaling organizations, defining culture, establishing product vision, resolving misalignment, creating strategic clarity, or setting behavioral standards. Use when user mentions North Star, team values, mission, principles, guardrails, decision framework, or cultural alignment.
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
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.
Use to convert probabilities into decisions (bet/pass/hedge) and optimize scoring. Invoke when need to calculate edge, size bets optimally (Kelly Criterion), extremize aggregated forecasts, or improve Brier scores. Use when user mentions betting strategy, Kelly, edge calculation, Brier score, extremizing, or translating belief into action.
Use when starting technical work requiring structured approach - writing tests before code (TDD), planning data exploration (EDA), designing statistical analysis, clarifying modeling objectives (causal vs predictive), or validating results. Invoke when user mentions "write tests for", "explore this dataset", "analyze", "model", "validate", or when technical work needs systematic scaffolding before execution.
Use when documenting significant technical or architectural decisions that need context, rationale, and consequences recorded. Invoke when choosing between technology options, making infrastructure decisions, establishing standards, migrating systems, or when team needs to understand why a decision was made. Use when user mentions ADR, architecture decision, technical decision record, or decision documentation.
Use when designing visual interfaces, data visualizations, educational content, or presentations and need to ensure they align with how humans naturally perceive, process, and remember information. Invoke when user mentions cognitive load, visual hierarchy, dashboard design, form design, e-learning, infographics, or wants to improve clarity and reduce user confusion. Also applies when evaluating existing designs for cognitive alignment or choosing between design alternatives.