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Found 52 Skills
Apple Silicon skill for M-series development and profiling. Use when leveraging unified memory, Metal Performance Shaders, Instruments profiling, sysctl hardware queries, Rosetta 2 behavior, or 16KB page size considerations. Activates on queries about Apple Silicon, unified memory, AMX, MPS, Instruments, Rosetta, or M-series page size.
Process large datasets efficiently using chunk(), chunkById(), lazy(), and cursor() to reduce memory consumption and improve performance
Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing"
Optimizing .NET allocations/throughput. Span, ArrayPool, ref struct, sealed, stackalloc.
万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。
Use when a Unity 6.3 game is slow or stutters: low fps, frame spikes, hitches when entering areas or on first effects, GC spikes, too many draw calls or SetPass calls, CPU vs GPU bound questions, Profiler, Profile Analyzer, Memory Profiler, Frame Debugger or Project Auditor work, GPU Resident Drawer or SRP Batcher setup, LOD and Mesh LOD, shader warm-up and variants, memory or VRAM budgets, IL2CPP and build size, or proving a fix with numbers from a player.
Reclaim DRAM by disabling unused subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB. Use for headless or no-camera Jetson deployments; not for CPU/GPU frequency tuning.
Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM fixes.
Conserve memory by reusing existing instances when working with large numbers of similar objects.
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
Performance diagnosis and optimization - MicroProfiler, Script Profiler, Developer Console, Scene Analysis, Luau heap and memory categories, memory leaks, network/replication cost, rendering and physics cost, streaming, native codegen, Parallel Luau with Actors. Use when a game lags, stutters, drops FPS, crashes on mobile, has high ping, or before optimizing hot code.
Analyze and optimize Roblox scene and script performance. Use for mobile frame rate, memory, instance count, rendering cost, physics, particles, lighting, asset budgets, streaming, leaks, and using the rbx-scene-analysis workflow.