Skill UI

This advanced assistant profiles specified targets (scripts, processes, GPU, memory, etc.) to identify performance bottlenecks. It selects appropriate profiling strategies, runs external tools (e.g., cProfile, nvidia-smi), and can write code instrumentation to measure CPU, GPU, memory, and interconnect overheads. It generates a detailed, actionable report.

This expert tool provides deep, systematic auditing of datasets to assess completeness, consistency, accuracy, and structural validity. It performs full data profiling, detects anomalies (outliers), analyzes missing data mechanisms (MCAR/MAR/MNAR), and calculates a Data Quality Score (DQS). Use it when validating data for model training, debugging pipelines, or establishing ongoing monitoring checks.

This skill acts as a Consumer Psychologist, building deep psychographic profiles by analyzing desires, fears, identity commitments, and underlying worldview. It moves beyond basic demographics to uncover the emotional drivers and core needs that shape consumer behavior. Ideal for pre-positioning, developing persuasive copy, and designing effective funnels.

This tool enables deep inspection and validation of web applications by connecting to the browser's DevTools Protocol (MCP). It allows agents to perform tasks like DOM inspection, capturing console logs, monitoring network requests, profiling performance, and taking screenshots in a live environment. Essential for debugging UIs, validating API integrations, and performing end-to-end automated testing.

This skill provides a comprehensive framework for measuring Go application performance. It guides users through writing robust benchmarks using `testing.B`, running tests with various flags (`-benchmem`, `-cpuprofile`), interpreting complex profiling data (pprof), statistically comparing results using tools like `benchstat`, and setting up CI regression detection. It is essential for deep performance analysis and making statistically sound optimization decisions.

A comprehensive skill for engineering high-quality, observable Go services. It guides best practices across five key signals: structured logging (slog), Prometheus metrics, OpenTelemetry tracing, continuous profiling (pprof), and RUM. Use this when instrumenting new features, reviewing PRs, or auditing entire codebases to ensure systems are fully measurable for reliable diagnosis and alerting.

A comprehensive guide covering advanced optimization techniques for Golang, including allocation reduction, CPU cycle efficiency, memory layout tuning, Garbage Collection (GC) management, pooling, and caching strategies. This skill provides a systematic methodology (Measure -> Hypothesize -> Improve -> Benchmark) for resolving bottlenecks identified through profiling tools like pprof or fgprof, ensuring optimizations are targeted and validated.

A Lodash-inspired, generics-first utility library providing 500+ type-safe functions for common data transformations in Go. It eliminates boilerplate code associated with manual loops, offering declarative methods like Map, Filter, Reduce, and GroupBy. The library supports core immutable operations (lo), concurrent variants (lop), mutable mutations (lom), and lazy iterators (loi), allowing developers to choose the optimal approach based on performance profiling and memory constraints. Ideal for implementing robust, type-safe data pipelines.

A systematic guide for debugging complex issues in Go applications, including crashes, deadlocks, concurrency errors, and performance bottlenecks. This skill teaches the 'Golden Rules' of debugging: reproducing bugs, isolating variables, and finding the true root cause rather than applying symptom fixes. It covers advanced techniques using pprof for profiling, the Delve debugger (dlv), and Go's built-in race detector, providing a structured methodology for professional software development.

This skill provides expert-level control over a live Chrome browser. It enables full web automation (clicking, form filling, navigation), deep debugging (analyzing console logs, network requests), visual inspection (screenshots, snapshots), and detailed performance profiling. Ideal for QA engineers, web scraping, and front-end development testing.

This tool functions as an expert competitive intelligence analyst. It takes a list of competitor URLs and generates comprehensive, structured profile documents. It combines live site scraping (e.g., features, pricing, value prop), SEO metrics, and third-party review data (G2, Capterra) to provide deep, actionable insights. Ideal for market research, product comparison, and strategic competitive planning.

A comprehensive methodology for offensive security, red team intelligence gathering, and bug bounty reconnaissance. Covers domain recon, email harvesting, social media profiling, code leaks, infrastructure mapping, cryptocurrency tracing, and geospatial intelligence. Essential for building detailed attack-surface maps against organizations or individuals.