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Found 51 Skills
Improve code performance without changing behavior. Use when code fails latency/throughput requirements. Covers profiling, caching, and algorithmic optimization.
Comprehensive code reviewer for Java and Python implementations focusing on correctness, efficiency, code quality, and algorithmic optimization. Reviews LeetCode solutions, data structures, and algorithm implementations. Use when reviewing code, checking solutions, or providing feedback on implementations.
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
Analyze development sessions, capture learnings, and improve Claude Code instructions. Use when the user wants to reflect on a session, improve CLAUDE.md, extract learnings, or optimize AI-human collaboration. Supports two modes: quick (default) focuses on CLAUDE.md improvements, deep mode performs comprehensive session analysis with learning capture.
Set up and run an autonomous experiment loop for any optimization target. Use when asked to start autoresearch or run experiments.
Agent skill for refinement - invoke with $agent-refinement
Split your code into smaller bundles to reduce initial load time and improve performance.
Follow this sub-process for code optimization — handle tasks where 'behavior remains unchanged but structure changes' (structure / performance / readability). Shift single-module internal optimization from 'AI random refactoring' to 'first scan to generate a checklist, confirm each item with the user, execute step by step according to the method library, and obtain manual approval for each step'. Trigger scenarios: When the user mentions phrases like 'optimize / refactor / rewrite / split / poor performance / too long code' without any accompanying behavior changes. Do not handle new requirements (route to feature), bugs (route to issue), or cross-module architecture restructuring (route to architecture + decisions).
Workflow for measuring and optimizing the ACIR circuit size of a constrained Noir program. Use when asked to optimize a Noir program's gate count or circuit size.
Guidance on Python code style optimization and Pythonic idioms; Based on the complete content of *One Python Craftsman* and the "Friendly Python" concept, covering variable naming, control flow, data types, container types, function design, exception handling, decorators, file operations, and SOLID principles; Providing user-friendly and maintainer-friendly design patterns, review checklists, and over 140 practical templates
Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings.
LLVM IR and pass pipeline skill. Use when working directly with LLVM Intermediate Representation (IR), running opt passes, generating IR with llc, inspecting or writing LLVM IR for custom passes, or understanding how the LLVM backend lowers IR to assembly. Activates on queries about LLVM IR, opt, llc, llvm-dis, LLVM passes, IR transformations, or building LLVM-based tools.