华为昇腾 Ascend Extension for PyTorch (torch_npu) 的环境检查、部署与能力指引。在用户使用 @torch_npu、昇腾 NPU、CANN、或需要将 PyTorch 迁移到 NPU 时自动应用；当用户使用 @torch_npu_doc 时，基于 skill 的 reference 文档提供项目内中文文档能力说明。
Plugin torch_npu from marketplace awesome-ascend-skills in ascend-ai-coding/awesome-ascend-skills. Commands read from the repo's manifest — 30 days ago.
torch_npu华为昇腾 Ascend Extension for PyTorch (torch_npu) 的环境检查、部署与能力指引。在用户使用 @torch_npu、昇腾 NPU、CANN、或需要将 PyTorch 迁移到 NPU 时自动应用；当用户使用 @torch_npu_doc 时，基于 skill 的 reference 文档提供项目内中文文档能力说明。
AI for Science skill set for Huawei Ascend NPU. Includes a main routing skill for profiling collection, model migration, and TensorFlow route selection, plus specialized leaf skills for Boltz2, BoltzGen, DeepFRI, DiffSBDD, GENERator, OligoFormer, ProteinBERT, TensorFlow Community deployment, TF-to-PyTorch conversion, and torch_npu profiling workflows.
191 skills
官方推荐的 AI for Science 安装包。适用于 AI for Science 场景下的 Profiling 采集、模型迁移、TensorFlow/Keras 路线选择与相关子方向能力。
191 skills
官方推荐的昇腾基础安装包。适合新同学和通用项目起步，包含设备检查、容器环境与 PyTorch NPU 基础能力。建议作为所有场景的第一步安装入口。
191 skills
官方推荐的昇腾推理安装包。适用于模型转换、量化、推理部署与评测场景，包含 ATC、vLLM-Ascend、ais-bench、msmodelslim、Diffusers 与 Wan 适配相关 skills。
191 skills
官方推荐的昇腾算子开发与迁移安装包。适用于 AscendC 算子开发、torch_npu 自定义算子接入、Triton-Ascend 迁移与算子基准测试场景。
191 skills
官方推荐的昇腾 Profiling 与性能分析安装包。适用于 Profiling 数据采集、瓶颈分析、训练性能诊断与 MFU 分析场景。
191 skills
Automated code review for pull requests using multiple specialized agents with confidence-based scoring to filter false positives
1 command
Claude Skills for Obsidian
6 skills
Personalized AWS guidance built on patterns from 350,000+ startups. Get architecture, cost, and security recommendations matched to your stage, from day-one account setup to production-ready infrastructure. Migrate to AWS from Azure, GCP, or Heroku with resource discovery, cost estimates, and generated Terraform. Move OpenAI, Azure OpenAI, and Gemini code to Amazon Bedrock, and plan and prototype AI agents on AgentCore and other AWS runtimes. Includes AWS Activate credits eligibility, 60+ exclusive startup offers, and multi-account, multi-region support. Built by AWS Startup Solutions Architects.
13 skills · 1 command · 7 agents · 1 MCP server
Triage tickets, draft responses, escalate issues, and build your knowledge base. Research customer context and turn resolved issues into self-service content.
5 skills · 8 MCP servers
Personal knowledge brain for your coding agent — hybrid search, synthesis, and durable cross-session memory, plus a curated brain-first skill set.
80 skills · 1 MCP server · hooks
Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork), clinical-research (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.
6 skills · 7 commands · 2 agents
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.