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Found 222 Skills
Choose and implement effector-storage persistence patterns for Effector apps. Use when tasks involve persist/createPersist usage, selecting adapters (local/session/query/broadcast/storage/asyncStorage/memory/nil/log), configuring clock/pickup/context/keyPrefix, validating data with contracts, handling done/fail/finally flows, SSR-safe adapter fallback with either, or debugging sync and serialization issues.
Design state schemas, implement reducers, configure persistence, and debug state issues for LangGraph applications. Use when users want to (1) design or define state schemas for LangGraph graphs, (2) implement reducer functions for state accumulation, (3) configure persistence with checkpointers (InMemorySaver/MemorySaver, SqliteSaver, PostgresSaver), (4) debug state update issues or unexpected state behavior, (5) migrate state schemas between versions, (6) validate state schema structure, (7) choose between TypedDict and MessagesState patterns, (8) implement custom reducers for lists, dicts, or sets, (9) use the Overwrite type to bypass reducers, (10) set up thread-based persistence for multi-turn conversations, or (11) inspect checkpoints for debugging.
State persistence patterns for autonomous-dev including JSON persistence, atomic writes, file locking, crash recovery, and state versioning. Use when implementing stateful libraries or features requiring persistent state.
Durable UI patterns for modern web development — persisting client-side state across page loads, browser sessions, and shareable URLs. Use this skill when implementing localStorage persistence, URL query parameter state, form draft auto-save, multi-step wizard persistence, click-outside dismissal, modal/dialog backdrop patterns, or any client-side state and interaction pattern that should be resilient and well-behaved. Works with React, Vue, and Svelte.
Yida Platform Login State Management Skill, manages login state via Playwright (Cookie Persistence + QR Code Login) and retrieves CSRF Token.
Autonomous AI Project Agent & Cron Task Runner. Orchestrates repetitive AI-driven engineering tasks with state persistence (Memory) and advanced workflow controls.
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.
Sets up a Ralph autonomous development loop for any project. First generates a full PRD from the user's description, then derives a task plan from it. Wraps Claude Code in an intelligent while-true loop with circuit breakers, exit detection, session persistence, and progress tracking. Use when you want Claude to autonomously work through a task list until done.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.