Generate and convert VeADK agent code from requirements, Langchain/Langgraph code, or Dify workflows.
npx skills add https://github.com/kbtime/openclaw-workspace --skill veadk
Please help me install this Agent Skill. Skill: VeADK 技能集合 Source: https://github.com/kbtime/openclaw-workspace/tree/main/skills/veadk-skills Command: npx skills add https://github.com/kbtime/openclaw-workspace --skill veadk
This Skill helps developers and engineers create, convert, and refine VeADK Agent implementations from user requirements, existing Langchain/Langgraph code, or Dify workflow definitions, reducing manual translation and boilerplate work.
Generate a VeADK Agent that converts my Langchain chatbot into a VeADK agent with a root_agent, appropriate sub_agents, and save generated files using the provided save_file script.
High-intent search queries and answers about installing and using this skill.
Converting Langchain code to VeADK agent code involves mapping your existing Langchain or Langgraph project structures into root_agent and sub_agent definitions using automated mapping rules. This process translates your current chatbot logic into orchestrated VeADK agents.
Migrating a Dify workflow into VeADK agents is supported by translating Dify YAML workflow definitions into structured VeADK agent code. The conversion generates root_agent and sub_agent architectures, optimizing system prompts for production automation.
Structuring VeADK agents for automation requires defining a root_agent and appropriate sub_agents following VeADK conventions, configuring structured Pydantic response formats, and integrating knowledgebases. This architecture ensures consistent production behavior for automated services.
VeADK supports structured Pydantic responses by allowing you to configure model_extra_config for your agents. This feature enforces consistent structured outputs from your LLM agents, which is essential for reliable knowledge-driven services.
Saving generated VeADK agent files is handled automatically using the provided save_file script. After generating root_agent and sub_agent definitions from your requirements or converted code, the script persists these files directly to your project directory.
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