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This skill helps you choose and pair web typography for readability and performance, guiding line length, hierarchy, and responsive loading.
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👾 Open Computer Use – Open-Source Alternative to Codex Computer Use
Foundation framework for building multi-step agents with built-in planning, memory, and skill delegation. Provides six core middleware options: task planning, filesystem context management, subagent delegation, persistent memory, human approval workflows, and on-demand skill loading Includes three always-present built-in tools: write_todos for task tracking...
Orchestrate subagents, plan multi-step tasks, and require human approval for sensitive operations. Delegate work to specialized subagents via the task tool; custom subagents support isolated tool sets and system prompts, while the default "general-purpose" subagent inherits main agent configuration Plan and track complex workflows with write_todos , organiz...
Framework selection guide for LangChain, LangGraph, and Deep Agents layered architecture. Layered frameworks where LangChain provides foundation primitives, LangGraph adds orchestration and control flow, and Deep Agents adds planning, memory, file management, and skill delegation Decision table guides framework choice based on task complexity: LangChain for...
LangChain ecosystem package versions, dependencies, and installation guidance for Python and TypeScript. Start all new projects on LangChain 1.0 LTS; version 0.3 is legacy maintenance-only. Always install langchain-core explicitly alongside other packages. Choose one orchestration layer: LangGraph for fine-grained graph control, or Deep Agents for batteries...
Build production LangChain agents with create_agent(), tools, and middleware patterns. Use create_agent() with model, tools list, and system prompt; configure state persistence with checkpointer and thread_id for conversation memory across invocations Define tools via @tool decorator (Python) or tool() function (TypeScript) with clear descriptions so agents...
Directed graph framework for building stateful, multi-step agent workflows with fine-grained control. StateGraph with typed state schemas, reducers for accumulating lists/values, and nodes that return partial state updates Static edges for fixed flow, conditional edges for branching, and Command for combining state updates with dynamic routing Send API for...
Pause graph execution for human review, approval, or validation, then resume with their input. Requires three components: a checkpointer (InMemorySaver or PostgresSaver), a thread ID in config, and JSON-serializable interrupt payloads interrupt(value) pauses and surfaces data; Command(resume=value) resumes and returns that value to the paused node All code...
Durable graph execution with thread-scoped checkpoints, state history, and cross-thread long-term memory. Three checkpointer options: InMemorySaver for testing, SqliteSaver for local development, PostgresSaver for production; always pass thread_id in config to enable persistence Browse and replay from past checkpoints using get_state_history() , fork execut...
The .NET library to build AI agents with 30+ built-in connectors.
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4771 candidates for Data. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
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