unsloth-kernel-optimization
Optimize and implement GPU kernels using CubeCL for memory-efficient LLM training
Find the perfect capability for your agent.
Optimize and implement GPU kernels using CubeCL for memory-efficient LLM training
Otimizador automático de código usando análise evolutiva GEPA para melhorar qualidade, performance e manutenibilidade
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use for ML training, analytics tools, performance profiling, or any Python heavy lifting.
Analyze the competitive and adjacent solution landscape to surface differentiation opportunities.
High-performance C development for data-intensive systems, with explicit emphasis on time-indexed / log-structured in-memory engines (e.g., Timelog-class designs). Use when building advanced data structures, algorithms, or libraries in C with focus on: memory efficiency, cache locality, immutable segment layouts, atomic publication, snapshot reads, SIMD/bit operations, and (future) Python bindings. Applies to: custom allocators, paged/segment storage, compression and bitmaps, index structures, single-writer/multi-reader concurrency patterns, background maintenance (flush/compaction), and performance-critical library development.
Debug PyTorch issues systematically. Use when encountering tensor errors, CUDA out of memory errors, gradient problems like NaN loss or exploding gradients, shape mismatches between layers, device conflicts between CPU and GPU, autograd graph issues, DataLoader problems, dtype mismatches, or training instabilities in deep learning workflows.
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use for ML training, analytics tools, performance profiling, or any Python heavy lifting.
Protocol untuk meningkatkan kecerdasan, presisi, dan keamanan dalam coding dan debugging.
Assert CPU-only runtime inside a container using PyTorch (torch.cuda.is_available()==False) and optional env var checks. Use to prevent accidental GPU execution during CPU smoke tests.
统一开发编排器:将 Superpowers 方法论框架与 AI 代码工厂深度整合, 创建统一的开发工作流,结合 TDD 纪律、SoT 合规和自动化代码生成。
Audit and remove unnecessary abstractions from the codebase. Use when user wants to simplify, reduce dependencies, or eliminate complexity that slows down AI agents.
Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers multi-node setup, checkpointing, and process management using torchrun. (ddp, fsdp, distributeddataparallel, torchrun, nccl, rank, process-group)
Expert embedded systems engineer specializing in microcontroller programming, RTOS development, and hardware optimization. Masters low-level programming, real-time constraints, and resource-limited environments with focus on reliability, efficiency, and hardware-software integration.
Rust 1.92+ development specialist covering Axum, Tokio, SQLx, and memory-safe systems programming. Use when building high-performance, memory-safe applications or WebAssembly.
Fix CuPy NVRTC compilation errors on Windows. Trigger: NVRTC_ERROR_BUILTIN_OPERATION_FAILURE, nvrtc-builtins64 not found
Takes the dual of a linear program (LP). Use when the user provides an LP in LaTeX or markdown and wants its dual, or asks about LP duality transformations.
Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.
Use when creating or editing reveal.js presentations, or when user mentions slides, presentations, reveal.js, code examples in slides, speaker notes, or slide design - enforces Tailwind CSS, proper code sizing, progressive reveal, semantic colors, and timing markers
Senior expert in Tailwind CSS 4.0, CSS-First architecture, and modern Design Systems.