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Found 51 Skills
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).
Analyze code for performance and efficiency improvements
Supports automatic generation/optimization/fixation/checking of index files to ensure all index files (index.ts / index.js) comply with the barrel export specification. Core principle: All index files must follow the barrel export specification.
Set up and run an autonomous experiment loop for any optimization target. Use when asked to start autoresearch or run experiments.
Create ShinkaEvolve task scaffolds from a target directory and task description, producing `evaluate.py` and `initial.<ext>` (multi-language). Use when asked to set up new ShinkaEvolve tasks, evaluation harnesses, or baseline programs for ShinkaEvolve.
Agent skill for refinement - invoke with $agent-refinement
Automatically analyze performance issues when user mentions slow pages, performance problems, or optimization needs. Performs focused performance checks on specific code, queries, or components. Invoke when user says "this is slow", "performance issue", "optimize", or asks about speed.
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
[Hyper] Optimize an existing codebase through baseline-first experiments, binary evaluation, and one-mutation-at-a-time iteration. Use for codebase autoresearch, measured bottleneck reduction, benchmarked code optimization, and evidence-backed refactors.
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.
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.