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Found 1,575 Skills
Enterprise engineering standards for Angular: Functional Interceptors, SASS/BEM styling, and strict testing (85% coverage).
Enterprise testing standards for Angular: Unit tests, mocking, and minimum 85% coverage requirements.
Configures the Unlayer editor — feature flags, appearance, theming, merge tags, design tags, display conditions, special links, HMAC security, file storage, image uploads, localization, custom fonts, validation.
Builds custom drag-and-drop tools for the Unlayer editor — registering tools, adding property editors, creating custom widgets, head CSS/JS injection, tool configuration, and the custom# prefix convention.
Testing strategy for Supabase Studio. Use when writing tests, deciding what type of test to write, extracting logic from components into testable utility functions, or reviewing test coverage. Covers unit tests, component tests, and E2E test selection criteria.
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Claude, Gemini, Llama), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
Captures quality metrics baseline (tests, coverage, type errors, linting, dead code) by running quality gates and storing results in memory for regression detection. Use at feature start, before refactor work, or after major changes to establish baseline. Triggers on "capture baseline", "establish baseline", or PROACTIVELY at start of any feature/refactor work. Works with pytest output, pyright errors, ruff warnings, vulture results, and memory MCP server for baseline storage.
This skill should be used when auditing a codebase for AI agent readiness, or when guiding improvements to make a codebase work well with agentic coding tools. It applies when users ask to evaluate test coverage, file structure, type system usage, dev environment speed, or automated enforcement -- the five pillars that determine how effectively coding agents can operate in a project. Triggers on "audit my codebase", "make this agent-ready", "improve for AI agents", "agent-friendly", or questions about why agents struggle with a codebase.
Configures comprehensive testing in Gradle including JUnit 5, TestContainers, test separation (unit vs integration), and code coverage with JaCoCo. Use when asked to "set up JUnit 5", "configure TestContainers", "separate integration tests", or "add code coverage". Works with build.gradle.kts, test source sets, and CI/CD configurations.
A skill that equips you with real-time, source-grounded web search and content retrieval using the Exa API—optimized for balanced relevance and speed (type="auto") and full-text extraction for downstream reasoning, RAG, and code assistance. Powering agents with fast, high-quality web search by Exa.AI.
Review PyTorch pull requests for code quality, test coverage, security, and backward compatibility. Use when reviewing PRs, when asked to review code changes, or when the user mentions "review PR", "code review", or "check this PR".
New Feature Design Exploration Process. Used when users have vague ideas for new features or modules. Through the structured process of "Requirements Convergence → Technical Research → ASCII Batch Exploration → HTML Design Draft → Full State Coverage → Requirements Summary", deliverable design reference documents are generated from vague ideas, serving as input for the PRD phase.