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Found 9,224 Skills
Apply meta-analysis to synthesize effect sizes across multiple studies, assess heterogeneity, and evaluate publication bias. Use this skill when the user needs to combine findings from prior research, compare fixed-effect vs random-effects models, compute pooled effect sizes, or when they ask 'what does the overall evidence say', 'how do I combine results across studies', or 'is there publication bias'.
Apply auction theory to compare the four canonical auction formats and assess revenue equivalence. Use this skill when the user needs to choose an auction format, evaluate bidding strategies, or determine when revenue equivalence breaks down due to risk aversion, asymmetry, or correlated values.
Apply rigorous survey design principles including construct operationalization, Likert scale development, reliability and validity assessment, and common method variance control. Use this skill when the user designs questionnaires, develops measurement items, needs to evaluate Cronbach's alpha or AVE, or when they ask 'how do I operationalize this construct', 'is my scale reliable', or 'how do I control for CMV'.
Review business contracts for risk identification including liability clauses, IP ownership, termination terms, and payment conditions. Use this skill when the user needs a practical contract risk assessment for vendor agreements, partnership contracts, or service agreements — even if they say 'review this contract', 'what should I watch out for', 'is this agreement fair', or 'negotiate better terms'.
Combine multiple forecasting models into ensemble predictions for improved accuracy. Use this skill when the user needs to improve forecast reliability, combine ARIMA/Prophet/ETS outputs, or build a robust forecasting pipeline — even if they say 'combine forecasts', 'model averaging', or 'which forecast should I trust'.
Apply Actor-Network Theory (Latour, Callon) to trace how human and non-human actors (actants) form networks through translation processes. Use this skill when the user needs to map sociotechnical assemblages, analyze how innovations stabilize or fail through network-building, trace the four moments of translation (problematization, interessement, enrollment, mobilization), or when they ask 'how did this technology become accepted', 'who and what holds this network together', or 'why did this innovation fail to gain traction'.
Extract the full design language from any website URL. Produces 8 output files including AI-optimized markdown, visual HTML preview, Tailwind config, React theme, shadcn/ui theme, Figma variables, W3C design tokens, and CSS variables. Also runs WCAG accessibility scoring. Use when user says 'extract design', 'get design system', 'design language', 'design tokens', 'what colors/fonts does this site use', or '/extract-design'.
Scan code for security vulnerabilities and secrets. Detect exposed secrets, insecure patterns, and common vulnerabilities.
Use when operating production Kubernetes — Helm, autoscaling (HPA/VPA), resource management, StatefulSets, external-secrets, observability (Prometheus/Grafana/Loki), RBAC, Pod Security Standards, NetworkPolicies, admission control, backup (Velero), and cost control.
When the user wants to optimize food and beverage supply chains, manage perishability, ensure food safety, or handle retail distribution. Also use when the user mentions "food supply chain," "beverage distribution," "HACCP," "food safety," "perishable logistics," "shelf life management," "FEFO," "farm to fork," "CPG distribution," "grocery supply chain," or "fresh produce logistics." For retail allocation, see retail-allocation. For promotional planning, see promotional-planning.
When the user wants to implement shipment tracking, product traceability, or supply chain visibility. Also use when the user mentions "tracking," "traceability," "visibility," "serialization," "lot tracking," "batch tracking," "chain of custody," "provenance," "track and trace," or "shipment monitoring." For control towers, see control-tower-design. For compliance, see compliance-management.
Analyzes code comments for accuracy, completeness, and long-term maintainability. Identifies misleading comments, comment rot, and documentation gaps. Triggers: After adding documentation, before finalizing a PR, when reviewing comments. Examples: - "Check if the comments are accurate" -> verifies comments match code behavior - "Review the documentation I added" -> analyzes new comments for quality - "Analyze comments for technical debt" -> finds outdated or misleading comments - "Are my docstrings correct?" -> validates documentation accuracy