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Found 2,493 Skills
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
Write comprehensive unit tests with high coverage using testing frameworks like Jest, pytest, JUnit, or RSpec. Use when writing tests for functions, classes, components, or establishing testing standards.
Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
Test automation framework expert for creating and maintaining automated tests. Use when user asks to write tests, automate testing, or improve test coverage.
Analyze code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.
Test Node.js applications with Jest including unit tests, integration tests, mocking, code coverage, and CI/CD integration
Execute and troubleshoot memory-cli commands for episode management, pattern analysis, and storage operations. Use this skill when running CLI commands, debugging CLI issues, explaining command usage, or guiding users through CLI workflows.
Use when creating, listing, inspecting, or deleting Tigris Storage buckets
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
Use when writing unit/integration tests for Vite projects - provides Vitest configuration, test APIs, mocking patterns, and coverage setup