Orchestrate LLM completions, memory windows, and tool calls for conversational AI workflows.
npx skills add https://github.com/copilot-ld/copilot-ld --skill libagent
Please help me install this Agent Skill. Skill: libagent Source: https://github.com/copilot-ld/copilot-ld/tree/main/packages/libagent Command: npx skills add https://github.com/copilot-ld/copilot-ld --skill libagent
libagent provides a modular library to orchestrate LLM-based agents by coordinating memory, completions, and tool execution to enable robust, multi-turn conversations and retrieval workflows.
Instantiate an AgentMind with memory, llm, and tool clients and run process on a sample interaction.
High-intent search queries and answers about installing and using this skill.
To build a multi-turn conversational AI agent, you orchestrate LLM completions, memory windows, and parallel tool calls using a modular library that coordinates memory management, resource indexing, and tool execution for robust chat interactions.
The best way to orchestrate retrieval-augmented generation pipelines is by coordinating LLM completions and memory windows with tool execution, enabling an end-to-end agent workflow across knowledge bases with streaming responses.
Parallel tool execution in AI agent workflows works by coordinating AgentHands with memory and LLM services, allowing multiple tool calls to process simultaneously during multi-turn conversations and retrieval workflows.
Yes, you can instantiate an AgentMind with your existing memory, LLM, and tool clients, integrating with libmemory, librpc, and libllm to run process on sample interactions for end-to-end agent workflows.
Yes, this agent orchestration library supports streaming responses and optional handoffs, coordinating LLM completions, memory windows, and tool calls to enable robust conversational AI workflows.
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