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Found 2,706 Skills
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
Configure pgvector extension for vector search in Supabase - includes embedding storage, HNSW/IVFFlat indexes, hybrid search setup, and AI-optimized query patterns. Use when setting up vector search, building RAG systems, configuring semantic search, creating embedding storage, or when user mentions pgvector, vector database, embeddings, semantic search, or hybrid search.
MUST READ before creating or enhancing any ADK agent project. Use when the user wants to build a new agent (e.g. "build me a search agent") or enhance an existing project (e.g. "add CI/CD to my project", "add RAG").
ALWAYS use when working with Angular CDK (Component Dev Kit), building custom accessible components, or using drag-drop, overlay, portal, or virtual scrolling.
Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".
Technical Document Knowledge Base (LLM Wiki) for Alibaba Cloud Tongyi Qianfan Platform. Activated when users inquire about Qianfan-related issues such as model lists, API parameters, error codes, application development (Agent/RAG/Knowledge Base/Memory/Plugins), model comparison and pricing, SDK/OpenAI compatible interfaces, multimodal capabilities (speech/image/video), Token billing, etc. It includes structured model market data in models (including contextWindow/QPM/pricing/sample code), wiki synthesis layer (topic pages/concept pages/comparison pages), and raw original document layer; for model specification issues, check models/index.md first, and for document-related issues, check wiki/index.md first.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
Offline-first mobile apps with local storage, sync queues, conflict resolution. Use for offline functionality, data sync, connectivity handling, or encountering sync conflicts, queue management, storage limits, network transition errors.
Meta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages). Deploy with HuggingFace or batch processing for RAG security.
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
Testing expert with comprehensive knowledge of test structure, mocking strategies, async testing, coverage analysis, and cross-framework debugging. Use PROACTIVELY for test reliability, flaky test debugging, framework migration, and testing architecture decisions. Covers Jest, Vitest, Playwright, and Testing Library.
Use when validating golden dataset quality. Runs schema checks, duplicate detection, and coverage analysis to ensure dataset integrity for AI evaluation.