发现 商业与营销 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
AI-driven test generation with mutation testing and property-based testing. Research shows property-based tests find 50x more bugs than unit tests. Use when: - Need comprehensive test coverage for new code - Co...
Mermaid diagram generation expert. Activate when: - User asks to create flowcharts, sequence diagrams, or architecture diagrams - User mentions "mermaid", "diagram", "visualize flow", "sequence diagram" - Need...
Use when building web interfaces for Microsoft Agent Framework agents. Triggers: "AG-UI", "agent UI", "agent web interface", "SSE streaming", "human-in-the-loop UI". NOT for: CLI-only agents or backend-only imp...
Use when implementing self-learning agent workflows. Triggers: "agent learning", "trajectory", "pattern recognition", "AgentDB", "self-learning agent". NOT for: Basic agent operations without learning requireme...
Use when building multi-agent workflows with Microsoft Agent Framework. Triggers: "workflow builder", "sequential workflow", "concurrent agents", "handoff", "group chat", "magentic". NOT for: Single-agent scena...
Tiered context management for multi-agent workflows. Use when: - Starting a new session and need to load project context - Context window approaching capacity (>70% usage) - Switching between different parts of...
C4 architecture diagram expert. Activate when: - User asks for architecture documentation - User mentions "C4 model", "system context", "container diagram", "component diagram" - Need to document system archite...
Use when working with Jujutsu (jj) version control. Triggers: "jj", "jujutsu", "revset", "bookmark", "rebase in jj", "jj workflow". NOT for: Standard git operations (use git commands directly).
Guide for writing pytest unit tests for the airline-discount-ml project. Use when asked to create, run, or debug Python unit tests for models, data access, or agents.
Instructions for starting the MCP Synth server (FastAPI) for synthetic data generation and tools.
Instructions for generating synthetic airline data with Synth CLI and loading it into SQLite.
Instructions for installing the Synth CLI (synthetic data generator) on macOS or Windows.
Process recipe photos into structured recipe data using GPT-4 vision. Use when asked to extract recipes from images, convert recipe photos to JSON, process HelloFresh/meal-kit recipe cards, or batch process mul...
Clean up Russian vocabulary CSV files from Italki lessons or tutoring sessions. Use when the user asks to clean up, format, or process a lesson CSV file.
Clean up Russian vocabulary CSV exports from Language Reactor (YouTube subtitle learning extension). Use when the user asks to process or clean up a Language Reactor CSV file.
Clean up Russian vocabulary CSV files from language exchange sessions. Use when the user asks to clean up, format, or process a language exchange CSV file.
Standard procedure for generating comprehensive pytest test suites following airline-discount-ml project patterns and test instructions.
Standard procedure for creating reusable pytest fixtures in conftest.py files for the airline-discount-ml project.
Standard procedure for checking test coverage using pytest-cov in the airline-discount-ml project.
Standard procedure for running pytest tests in the airline-discount-ml project with proper Python environment configuration.
Cross-platform GPU kernel dialect — write once, run on NVIDIA (CUDA), AMD (HIP), and Intel/others (OpenCL 1.2). Use when: (1) writing portable GPU code across CUDA/HIP/OpenCL, (2) porting CUDA kernels to AMD or...
Guidance for writing valid Emacs Lisp code with incremental validation. Use when writing or modifying elisp functions, especially complex nested forms with cl-loop, multiple let* bindings, or lambdas.
Proactively run GitHub Actions pipeline checks locally before pushing code. Use when making code changes to catch test, lint, and type-check failures early.
Strategies for debugging Emacs Lisp code, especially missing parentheses and Common Lisp compatibility issues. Use when encountering mysterious elisp errors or when working with literate elisp in org-mode files...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。