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Found 5,443 Skills
Executes Story Finalizer test tasks (label "tests") from Todo -> To Review. Enforces risk-based limits and priority.
Enforces constrained, opinionated styling patterns for gluestack-ui v4. Main overview skill that coordinates specialized sub-skills for setup, components, styling, variants, performance, and validation.
This skill should be used when the user asks to "create a lead magnet", "build a freebie", "PDF download", "checklist", "swipe file", "resource guide", or mentions lead magnets, opt-in incentives, or downloadable assets. Creates high-value lead magnets that convert and build trust.
Helps choose the right battery type and charging solution for Arduino/ESP32/RP2040 projects. Use when user asks about battery options, charging circuits, power source selection, or says "what battery should I use". Covers chemistry selection, safety, voltage regulation, and charging circuits.
Open-source password manager with self-hosting option.
Implement GitOps continuous delivery for Kubernetes using ArgoCD or Flux. Use for automated deployments with Git as single source of truth, pull-based delivery, drift detection, multi-cluster management, and progressive rollouts.
Conduct comprehensive, multi-round research that produces rich visual reports. Use when asked for "deep research", "comprehensive analysis", "compare frameworks", "evaluate options", "research the state of X", or any task requiring investigation across 10+ sources. NOT for quick lookups — this is a 5-15 minute deep dive that produces a briefing-quality artifact with screenshots, diagrams, tables, and cited findings.
Assigns confidence scores to agent outputs based on multiple factors including source quality, consistency, and reasoning depth. Produces calibrated confidence estimates. Activate on 'confidence score', 'how confident', 'certainty level', 'output confidence', 'reliability score'. NOT for validation (use dag-output-validator) or hallucination detection (use dag-hallucination-detector).
Understanding Reinforcement Learning from Human Feedback (RLHF) for aligning language models. Use when learning about preference data, reward modeling, policy optimization, or direct alignment algorithms like DPO.
Use after 2 consecutive failed attempts at solving a problem - STOP guessing and research documentation, codebase, and online resources before resuming
Guide for Next.js App Router dynamic routes and pathname parameters. Use when building pages that depend on URL segments (IDs, slugs, nested paths), accessing the `params` prop, or fetching resources by identifier. Helps avoid over-nesting by defaulting to the simplest route structure (e.g., `app/[id]` instead of `app/products/[id]` unless the URL calls for it).
Formal Design of Experiments (DOE) methodology for maximizing information from experiments while minimizing resources. Covers factorial designs, blocking, randomization, and optimal design strategies. Use when ", " mentioned.