Total 42,627 skills
Showing 12 of 42627 skills
AI for Science 场景下的昇腾 NPU Profiling 采集与性能分析 Skill，用于在华为 Ascend NPU 上使用 torch_npu.profiler 采集 L0、L1、L2 级性能数据，分析训练或推理中的算子耗时、调用栈、内存与瓶颈，并指导后续调优。
DeepFRI 的 TensorFlow 到 PyTorch 转换与昇腾 NPU 迁移 Skill，适用于蛋白质功能预测场景下的 TF 模型分析、PyTorch 重写、权重逐层映射、NPU 推理与精度验证，尤其适合需要在 Ascend 上运行 DeepFRI CNN 或 GCN 路径时使用。
MindSpeed-LLM 环境搭建指南，用于华为昇腾 NPU。覆盖 CANN 环境激活、PyTorch + torch_npu 安装、MindSpeed 加速库安装、Megatron-LM 核心模块集成、MindSpeed-LLM 安装及环境验证。当用户需要在昇腾 NPU 上搭建 MindSpeed-LLM 训练环境时使用。
将简单Vector类型Triton算子从GPU迁移到昇腾NPU。当用户需要迁移Triton代码到NPU、提到GPU到NPU迁移、Triton迁移、昇腾适配时使用。注意：无法自动迁移存在编译问题的算子。
SQL analysis skill for Ascend PyTorch Profiler / msprof DB (e.g., ascend_pytorch_profiler*.db, msprof_*.db). Convert natural language questions (operator latency, communication, dispatch, scheduling, schema/table queries) into safe and executable SQL, and extract table structure details from official documents as needed.
Codacy integration. Manage Repositories, Organizations. Use when the user wants to interact with Codacy data.
Use this skill when working with the UI5 Linter (@ui5/linter) for static code analysis of SAPUI5/OpenUI5 applications and libraries. Covers setup, configuring linting rules, running the linter to detect deprecated APIs, global variable usage, CSP violations, and manifest issues. Supports autofix for deprecated API usage, global references, event handlers, and manifest properties. Includes CI/CD integration, pre-commit hooks, and UI5 2.x migration preparation.
This skill provides comprehensive guidance for adapting Wan-series video generation models (Wan2.1/Wan2.2) from NVIDIA CUDA to Huawei Ascend NPU. It should be used when performing NPU migration of DiT-based video diffusion models, including device layer adaptation, operator replacement, distributed parallelism refactoring, attention optimization, VAE parallelization, and model quantization. This skill covers 9 major adaptation domains derived from real-world Wan2.2 CUDA-to-Ascend porting experience.
Comprehensive security auditor for AI agent skills, prompts, and instructions. Checks for typosquatting, dangerous permissions, prompt injection, supply chain risks, and data exfiltration patterns — before you use any agent or skill.
Teaches the data provider pattern using renderless components and scoped slots. Use when you need to abstract data fetching or state management logic and expose it to child components via slots.
Guides DeFi protocol security review and rug-risk assessment from public chain data, verified source, and historical patterns—covering EVM and Solana-style deployments, liquidity and tokenomics, governance centralization, bridges, exploit pattern matching, and evidence-structured audit reports. Use when the user asks for a DeFi security audit, rug risk analysis, contract vulnerability triage, LP lock verification, governance or upgrade risk, or cross-chain bridge review from observable data only.
Kerberos attack playbook for Active Directory. Use when targeting AD authentication via AS-REP roasting, Kerberoasting, golden/silver/diamond tickets, delegation abuse, or pass-the-ticket attacks.