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Found 2,831 Skills
Learning designer quality check for Canvas LMS courses. Audits module structure, content completeness, publishing state, date consistency, and rubric coverage. Use when asked to "QC a course", "is this course ready", "pre-semester check", or "quality review".
Implements Syncfusion WinForms SfDataGrid component for displaying and managing tabular data in Windows Forms applications. Use this when working with data grids, column management (auto-generation, stacked headers), data operations (filtering, sorting, grouping), or grid editing with validation. The skill covers data summaries, selection modes, export capabilities (Excel/PDF), conditional styling, master-detail views, and drag-and-drop functionality.
Overview The VC Attention Agent allows users to extract followings of top crypto VCs, including lists from Dragonfly, Paradigm, a16z, and more, to bypass manual mapping and identify where institutiona
Build React animations with Motion (formerly Framer Motion) - gestures (drag, hover, tap), scroll effects, spring physics, layout animations, SVG, exit animations, and motion values. Use when: building React animations, adding hover/tap/drag interactions, scroll-triggered effects, layout transitions, shared element animations, exit animations with AnimatePresence, or working with motion values and springs. Triggers: "animate", "motion component", "framer motion", "gesture", "drag", "scroll animation", "layout animation", "exit animation", "spring", "whileHover", "whileTap", "whileInView", "AnimatePresence", "layoutId", "useScroll", "useSpring", "useAnimate", "motion value", "reorder", "parallax".
Prevent Ethereum hashing bugs in JavaScript and TypeScript. Node's sha3-256 is NIST SHA3, not Ethereum Keccak-256, and silently breaks selectors, signatures, storage slots, and address derivation.
Kubernetes clusters, pods, nodes, workloads, storage, networking, and resource relationships. Query K8s inventory, diagnose degraded deployments and pod failures, investigate rollouts, audit ingress and network policies.
Diagnose, compare, and optimize Apache Spark applications and SQL queries using Spark History Server data. Use this skill whenever the user wants to understand why a Spark app is slow, compare two benchmark runs or TPC-DS results, find performance bottlenecks (skew, GC pressure, shuffle spill, straggler tasks), get tuning recommendations, or optimize Spark/Gluten configurations. Also trigger when the user mentions 'diagnose', 'compare runs', 'why is this query slow', 'tune my Spark job', 'benchmark comparison', 'performance regression', or asks about executor skew, shuffle overhead, AQE effectiveness, or Gluten offloading issues.
Heap exploitation playbook. Use when targeting ptmalloc2/glibc heap vulnerabilities including UAF, double free, overflow, off-by-one/null, and leveraging tcache/fastbin/unsortedbin attacks for arbitrary write or code execution.
Fetches live AI crypto trading signals with entry price, stop-loss, take-profit, leverage, confidence scores, and automated verification. Covers 50+ coins including BTC, ETH, SOL. Use when the user asks for crypto signals, trade ideas, market direction, portfolio analysis, or wants to build a trading bot.
Debug and emulate specific code fragments or functions using the Unicorn engine. Activate when the user wants to emulate a function with Unicorn, trace binary execution without running the full program, decrypt or decode data by emulating the algorithm, or bypass environment dependencies (JNI, syscalls, libc) during emulation.
Perform break-even analysis to determine the sales volume or revenue needed to cover all costs. Use this skill when the user needs to calculate break-even point, assess margin of safety, evaluate operating leverage, or decide pricing and volume trade-offs — even if they say 'how many units do we need to sell', 'when will we be profitable', or 'what happens if we lower the price'.
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'.