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Found 184 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。
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.
Catlass Operator End-to-End Development Orchestrator. Based on ascend-kernel (csrc/ops), it connects catlass design, catlass-operator-code-gen and ascendc sub-skills to complete the closed loop from project initialization to documentation, precision, and performance. Keywords: Catlass, end-to-end, ascend-kernel, operator development, workflow orchestration.
Interactive plan and diff review for AI coding agents. Visual browser UI for annotating agent plans — approve or request changes with structured feedback. Supports code review, image annotation, and auto-save to Obsidian/Bear Notes.
Ultimate Bug Scanner - Pre-commit static analysis for AI coding workflows. 18 detection categories, 8 languages, 4-layer analysis engine. The AI agent's quality gate.
Deploy, configure, and integrate Sandbox Agent - a universal API for orchestrating AI coding agents (Claude Code, Codex, OpenCode, Amp) in sandboxed environments. Use when setting up sandbox-agent server locally or in cloud sandboxes (E2B, Daytona, Docker), creating and managing agent sessions via SDK or API, streaming agent events and handling human-in-the-loop interactions, building chat UIs for coding agents, or understanding the universal schema for agent responses.
Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments
Write clear, plain-spoken code comments and documentation that lives alongside the code. Use when writing or reviewing code that needs inline documentation—file headers, function docs, architectural decisions, or explanatory comments. Optimized for both human readers and AI coding assistants who benefit from co-located context.
Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.
Voice conversations with Claude Opus 4.5 about your code projects. Receive calls from Claude or call Claude to discuss problems, brainstorm, and get code reviews.
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
Named Tmux Manager - Multi-agent orchestration for Claude Code, Codex, and Gemini in tiled tmux panes. Visual dashboards, command palette, context rotation, robot mode API, work assignment, safety system. Go CLI.