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Found 2,615 Skills
Build Retrieval-Augmented Generation (RAG) Q&A systems with Claude or OpenAI. Use for creating AI assistants that answer questions from document collections, technical libraries, or knowledge bases.
Apply Pragmatic Programmer (Hunt & Thomas, 2019 edition) advice to software tasks and code reviews; use when the user asks to apply pragmatic tips, asks how to approach a task, or when performing a code review to map relevant chapters/tips to the current context.
Read this skill to write, generate, or add test code. Trigger when: (1) user asks to write, add, create, or generate tests of any kind (unit tests, integration tests, API tests, E2E tests, Playwright tests, Vitest tests); (2) user has code with missing or zero tests and wants coverage; (3) user just implemented a new service, endpoint, feature, or module and needs tests for it; (4) user refactored code and wants to verify nothing broke with tests; (5) user wants to improve or expand existing test coverage. This skill produces complete, pyramid-shaped test suites — reads the code, selects only the necessary layers (unit/integration/API/E2E), and generates every file needed (schema tests, service tests, factories, helpers, cleanup utilities, spec files) following strict Vitest and Playwright patterns. Skip this skill when debugging failing tests, asking how to use testing APIs or tools, explaining testing concepts, configuring test runners, reviewing existing test code, or migrating between test frameworks.
Use when asking 'where should I store this data', 'should I use SwiftData or files', 'CloudKit vs iCloud Drive', 'Documents vs Caches', 'local or cloud storage', 'how do I sync data', 'where do app files go' - comprehensive decision framework for all iOS storage options
Check test coverage for unstaged changes. Use when user asks to "check coverage", "/coverage", or wants to see which unstaged changes lack test coverage.
Use when setting up @tigrisdata/storage in a new project or configuring authentication and bucket access
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
[Pragmatic DDD Architecture] Guide for creating PostgreSQL tables and defining relations using Drizzle ORM. Use when creating new schemas, managing PostgreSQL indexes, enums, mapping column names to camelCase for the domain, and explicitly exporting constraint names.
Evaluate test coverage and fill real gaps with high-value tests.
RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.
Retrieval-Augmented Generation - chunking strategies, embedding, vector search, hybrid retrieval, reranking, query transformation. Use when building RAG pipelines, knowledge bases, or context-augmented applications.
Evaluates RAG (Retrieval-Augmented Generation) pipeline quality across retrieval and generation stages. Measures precision, recall, MRR for retrieval; groundedness, completeness, and hallucination rate for generation. Diagnoses failure root causes and recommends chunk, retrieval, and prompt improvements. Triggers on: "audit RAG", "RAG quality", "evaluate retrieval", "hallucination detection", "retrieval precision", "why is RAG failing", "RAG diagnosis", "retrieval quality", "RAG evaluation", "chunk quality", "RAG pipeline review", "grounding check". Use this skill when diagnosing or evaluating a RAG pipeline's quality.