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feature-explorer
Discovers KrakenD features, checks edition availability (CE vs EE), and provides implementation examples
Skills IA testing security framework internals
Découvrez les skills testing security framework internals, comparez leurs dépôts et consultez leurs instructions.
Catégories: testing security framework internals
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Explorer
GitHub
mcp-serena-fast-ops
Fast code operations using Serena MCP (1-3s) for symbol search, memory read/write, and basic code editing in LoRAIro project
GitHub
collimator
Guide for using Collimator, a profunctor optics library for Lean 4. Use when writing code with lenses, prisms, traversals, or when accessing/modifying nested data structures.
GitHub
maturin-debugger
Diagnose and fix maturin build issues for PyO3 Python bindings. Use when encountering problems with maturin develop, missing Python exports, module registration errors, or type stub generation issues. Particula...
GitHub
rust-performance-analyzer
Analyzes Rust code for performance bottlenecks, memory inefficiencies, and optimization opportunities. Use when discussing performance, slow code, memory usage, profiling, benchmarks, or optimization.
GitHub
socket-programming
Low-level socket programming including BSD sockets, Winsock, and network byte manipulation
GitHub
io-multiplexing
High-performance I/O multiplexing including epoll, IOCP, kqueue, and io_uring
GitHub
using-jax
Applies JAX patterns for scientific Python development. Use when working with JAX, distrax, numpyro, blackjax, or scientific computing. Covers vmap, JIT, RNG handling.
GitHub
trait-generics
Master Rust traits, generics, and type system
GitHub
rust-macros
Master Rust macros - declarative and procedural macros
GitHub
plugin-optimization
Master plugin performance optimization, best practices, and marketplace readiness. Learn to optimize for speed, efficiency, and user satisfaction.
GitHub
advanced-topics
Explore advanced CS topics including advanced data structures, parallel computing, security, functional programming, and quantum computing.
GitHub
complexity-analysis
Analyze algorithm complexity, understand Big O notation, computability theory, NP-completeness, and computational limits.
GitHub
waldstorm
Use superpowers with more memory.
GitHub
rust-iterators
Leverage iterator chains for efficient, lazy data processing without intermediate allocations. Use when processing collections.
GitHub
rust-gpu-scheduling
Implement GPU scheduling with VRAM budgets, work queues, and model lifecycle management. Use when building ML pipeline orchestrators.
GitHub
rust-memory
Minimize allocations and cloning using references, Cow, and smart pointers. Use when optimizing hot paths or memory-constrained code.
GitHub
mithril-checkpoint-agent
Build mithril-checkpoint compression for PyTorch models. Use when implementing byte grouping, compression pipeline, or checkpoint I/O.
GitHub
mithril-cache-agent
Build mithril-cache for torch.compile caching. Use when implementing content-addressable storage, cache keys, eviction, or framework hooks.
GitHub
rust-ml-huggingface-porting
Port HuggingFace models to Candle with correct tensor naming. Use when debugging weight loading errors or matmul issues.
GitHub
rust-tokio-essentials
Core Tokio patterns including runtime setup, spawn_blocking for CPU work, and avoiding blocking operations. Use for any async Rust development.
GitHub
rust-pyo3-bridge
Bridge Rust and Python using PyO3 with proper GIL handling and async compatibility. Use when integrating Python ML models or libraries.
GitHub
assisting-reverse-engineering
Provides reverse engineering analysis support including function identification, data structure analysis, and behavior understanding. Use when analyzing unknown binaries, understanding program structure, or inv...
GitHub
detecting-integer-overflow
Detects integer overflow and underflow vulnerabilities in arithmetic operations used for buffer sizing or allocation. Use when analyzing calculations, size computations, or investigating integer wraparound issu...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.