GitHub
type-hints-for-ml-code
Apply appropriate type hints for ML/PyTorch code. Use when adding type annotations to ML code or addressing mypy errors.
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发现 tools framework internals 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
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GitHub
performance-optimization
Optimize training performance for Kaggle competitions. Use PROACTIVELY when training is slow, GPU memory issues occur, or user asks about performance tuning. Keywords: 遅い, 最適化, OOM, CUDA, batch_size, num_w...
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GitHub
seer
Set up GPU sandboxes for interpretability research. Use when writing setup.py scripts with Sandbox, SandboxConfig, ModelConfig, or create_notebook_session. Provides the exact API for Modal GPU environments - MU...
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GitHub
vibe-coding
AI-assisted development workflow with TDD, context management, and incremental implementation. Use when developing features with AI assistance, managing code context for AI tools, implementing features step-by-...
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GitHub
composable-rust-architecture
Expert knowledge for building event-driven systems with Composable Rust framework. Use when implementing reducers, designing state machines, working with effects, creating environment traits for dependency inje...
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GitHub
rust
Rust development patterns for video processing, trait abstractions, error handling, and Linux device interaction
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GitHub
performance-profiling
Structured performance profiling and optimization skill for identifying and eliminating bottlenecks. Auto-triggers on slowness keywords.
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GitHub
avoiding-non-null-assertions
Avoid non-null assertion operator (!) and use type-safe alternatives instead
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GitHub
quantum-analysis
Deep code and system analysis using the Quantum Cognitive OS. Use when analyzing code, architectures, or complex systems that benefit from multi-dimensional reasoning.
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GitHub
syntax-keyword-assert-perl
Use Syntax::Keyword::Assert for zero-cost assertions in Perl
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GitHub
kura-perl
Store and export type constraints for Type::Tiny, Moose, Data::Checks, and more
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GitHub
pure-data
Pure Data reference documentation for audio patch development. Use when writing .pd patches, working with OSC/audio/sampling, or implementing Pure Data code.
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GitHub
mmd-device-quad-cortex
Guide for using the Neural DSP Quad Cortex device library in MMD files. Use when the user mentions Quad Cortex, QC, Neural DSP guitar processor, or needs help with preset loading, scene switching, expression co...
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GitHub
fstar-verification
Comprehensive F* proof-oriented programming for formal verification including dependent types, refinement types, effect system, SMT solver integration, tactic-based interactive theorem proving, and verified cod...
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GitHub
result-simple-perl
Use Result::Simple for tuple-based error handling in Perl
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GitHub
performance-optimization-guide
Guides performance optimization: atomic clock service, performance monitoring, memory optimization, battery optimization. Use when optimizing performance, monitoring metrics, or improving app efficiency.
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GitHub
compound-engineering
Compound Engineering workflow for AI-assisted development. Use when planning features, executing work, reviewing code, or codifying learnings. Follows the Plan → Work → Review → Compound loop where each unit of...
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GitHub
chaos-compounding
Iteration 2 of Multiplicity Cascade - Amplifies jank recursively through iterations
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GitHub
openspec-agent
Implement features and tasks defined in openspec proposals.
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GitHub
implementing-python
Implements concise, streamlined Python code matching exact architect specifications. Use when writing Python code, creating modules, or when the user asks to implement features in Python.
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GitHub
add-new-aggregate-base-field
Add a new base field to an aggregate with clear rules for:
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GitHub
performance
Optimize code for speed and efficiency. Use this skill when profiling, identifying bottlenecks, or improving performance. Covers profiling tools, common patterns, and optimization strategies.
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GitHub
early-return-from-functions
avoids unnecessary computation
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GitHub
modular-monolith-designer
Define module boundaries, shared kernel, and anti-corruption layers.
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。