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Found 298 Skills
Use when debugging a Nemo Gym run or reward profiling job. Covers rollout collection failures, empty or partial JSONL outputs, stale materialized inputs, verifier/schema errors, Ray or Slurm issues, vLLM readiness, judge failures, tool/sandbox failures, cache problems, and throughput bottlenecks.
Debug Flutter applications systematically with this comprehensive troubleshooting skill. Covers RenderFlex overflow errors, setState() after dispose() issues, null check operator failures, platform channel problems, build context errors, and hot reload failures. Provides structured four-phase debugging methodology with Flutter DevTools, widget inspector, performance profiling, and platform-specific debugging for Android, iOS, and web targets.
Debug Angular applications systematically with expert-level diagnostic techniques. This skill provides comprehensive guidance for troubleshooting dependency injection errors, change detection issues (NG0100), RxJS subscription leaks, lazy loading failures, zone.js problems, and common Angular runtime errors. Includes structured four-phase debugging methodology, Angular DevTools usage, console debugging utilities (ng.probe), and performance profiling strategies for modern Angular applications.
Debug SwiftUI application issues systematically. This skill helps diagnose and resolve SwiftUI-specific problems including view update failures, state management issues with @State/@Binding/@ObservedObject, NavigationStack problems, memory leaks from retain cycles, preview crashes, Combine publisher issues, and animation glitches. Provides Xcode debugger techniques, Instruments profiling, and LLDB commands for iOS/macOS development.
Debug TensorFlow and Keras issues systematically. This skill helps diagnose and resolve machine learning problems including tensor shape mismatches, GPU/CUDA detection failures, out-of-memory errors, NaN/Inf values in loss functions, vanishing/exploding gradients, SavedModel loading errors, and data pipeline bottlenecks. Provides tf.debugging assertions, TensorBoard profiling, eager execution debugging, and version compatibility guidance.
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
Inspect and profile React Native component trees from agent-device. Use when debugging React Native props, state, hooks, render causes, slow components, excessive re-renders, or questions like why a component re-rendered.
Optimize the performance of your Flutter app
Analyze and optimize React component performance issues (slow renders, re-render thrash, laggy lists, expensive computations). Use when asked to profile or improve a React component, reduce re-renders, or speed up UI updates in React apps.
Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.
Analyses and optimises performance across frontend, backend and database interactions. Identifies bottlenecks and implements solutions to enhance speed and efficiency.
Profile a React Native Hermes app to measure re-render and CPU performance using argent profiler tools. Use when optimizing for performance, measuring before/after a fix, spotting slow components, diagnosing re-renders, checking CPU hotspots, or producing a ranked issue report.