Total 44,717 skills
Showing 12 of 44717 skills
Reviews Go code for idiomatic patterns, error handling, concurrency safety, and common mistakes. Use when reviewing .go files, checking error handling, goroutine usage, or interface design.
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
OpenTelemetry observability patterns: traces, metrics, logs, context propagation, OTLP export, Collector pipelines, and troubleshooting
Vitest testing framework patterns and best practices. Use when writing unit tests, integration tests, configuring vitest.config, mocking with vi.mock/vi.fn, using snapshots, or setting up test coverage. Triggers on describe, it, expect, vi.mock, vi.fn, beforeEach, afterEach, vitest.
Comprehensive debugging methodology for finding and fixing bugs (formerly debugging). This skill should be used when debugging code, investigating errors, troubleshooting issues, performing root cause analysis, or responding to incidents. Covers systematic reproduction, hypothesis-driven investigation, and root cause analysis techniques. Use when encountering exceptions, stack traces, crashes, segfaults, undefined behavior, or when bug reports need investigation.
Configure AWS Documentation MCP server to query up-to-date AWS knowledge, APIs, and best practices
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
UI/UX design systems specialist covering accessibility, icons, theming, design tokens, and user experience patterns. Use when user asks about design systems, WCAG accessibility compliance, ARIA patterns, icon libraries, dark mode theming, design tokens, or user experience research. Do NOT use for React component coding or frontend implementation (use moai-domain-frontend instead) or shadcn/ui specifics (use moai-library-shadcn instead).
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
Help users make better decisions between competing options. Use when someone is weighing pros and cons, comparing alternatives, struggling with a difficult choice, deciding between speed and quality, or asking "should we do X or Y?"
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.