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Found 51 Skills
Perform code optimization for .vue, .js, .css, .scss, .less files in Vue2 projects. By default, optimize git changed files, or execute according to the user-specified scope. Unify code structure, BEM styles, semantic naming and key comments to improve readability and collaboration efficiency. Do not generate new components or modify business logic. Trigger scenarios: Users request code optimization, code structure standardization, unified naming, Vue2 component optimization, and code style organization.
Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.
TypeScript code style and optimization guidelines. Use when writing TypeScript code (.ts, .tsx, .mts files), reviewing code quality, or implementing type-safe patterns. Triggers on TypeScript development, type safety questions, or code style discussions.
Profile application performance, identify bottlenecks, and optimize hot paths using CPU profiling, flame graphs, and benchmarking. Use when investigating performance issues or optimizing critical code paths.
Profile CPU usage to identify hot spots and bottlenecks. Optimize code paths consuming most CPU time for better performance and resource efficiency.
Karpathy-inspired autonomous research loop. Agent edits one file, evals, keeps or discards, repeats. Plateau-triggered web search breaks through ceilings. Git as state machine. Runs until stopped or budget exhausted.
Run metric-driven iterative optimization loops. Define a measurable goal, build measurement scaffolding, then run parallel experiments that try many approaches, measure each against hard gates and/or LLM-as-judge quality scores, keep improvements, and converge toward the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation. Inspired by Karpathy's autoresearch, generalized for multi-file code changes and non-ML domains.
Runtime performance audit worker (L3). Checks blocking IO in async, unnecessary allocations, sync sleep in async, string concat in loops, missing to_thread for CPU-bound, redundant data copies. Returns findings with severity, location, effort, recommendations.
Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations
Show ponytail's measured impact as a compact scoreboard: less code, less cost, more speed, from the benchmark medians. One-shot display, not a persistent mode, and not a per-repo number. Trigger: /ponytail-gain, "ponytail gain", "what does ponytail save", "show ponytail impact", "ponytail scoreboard".
Performance optimization specialist for improving application speed and efficiency. Use when investigating performance issues or optimizing code.
Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project.