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Found 39 Skills
Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while golang-performance provides the optimization patterns.
Give AI agents eyes into React apps - inspect component trees, props, state, hooks, and profile rendering performance from the command line
Optimizes a React Native app by profiling first to find real bottlenecks, then sweeping for mechanical issues. Entry-point for all performance work. Use when the app feels slow, user asks to optimize, fix re-renders, reduce jank, or improve startup. Delegates to argent-react-native-profiler for measurement.
Performance optimization guide for Capacitor apps covering bundle size, rendering, memory, native bridge, and profiling. Use this skill when users need to optimize their app performance.
Expert debugging workflows including print debugging (push_warning, push_error, assert), breakpoints (conditional breakpoints), Godot Debugger (stack trace, variables, remote debug), profiler (time profiler, memory monitor), error handling patterns, and performance optimization. Use for bug fixing, performance tuning, or development diagnostics. Trigger keywords: breakpoint, print_debug, push_error, assert, profiler, remote_debug, memory_leak, orphan_nodes, Performance.get_monitor.
Comprehensive testing and development workflow specialist combining DDD testing, characterization tests, performance profiling, code review, and quality assurance. Use when writing tests, measuring coverage, creating characterization tests, performing TDD, running CI/CD quality checks, or reviewing pull requests. Do NOT use for debugging runtime errors (use expert-debug agent instead) or code refactoring (use moai-workflow-ddd instead).
Systematic debugging approach for Rust async code with Tokio, Turso, and redb. Use when diagnosing runtime issues, performance problems, async deadlocks, database connection issues, or panics.
Advanced sub-skill for PyTorch focused on deep research and production engineering. Covers custom Autograd functions, module hooks, advanced initialization, Distributed Data Parallel (DDP), and performance profiling.
Debugging and troubleshooting Tokio applications using tokio-console, detecting deadlocks, memory leaks, and performance issues. Use when diagnosing async runtime problems.
Native macOS/iOS app performance profiling via xctrace/Time Profiler and CLI-only analysis of Instruments traces. Use when asked to profile, attach, record, or analyze Instruments .trace files, find hotspots, or optimize native app performance without opening Instruments UI.
Full Sentry SDK setup for Apple platforms (iOS, macOS, tvOS, watchOS, visionOS). Use when asked to "add Sentry to iOS", "add Sentry to Swift", "install sentry-cocoa", or configure error monitoring, tracing, profiling, session replay, or logging for Apple applications. Supports SwiftUI and UIKit.
Identify and debug performance regressions from code changes. Use comparison and profiling to locate what degraded performance and restore baseline metrics.