Best use case
veadk-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
根据用户的功能需求，完成与 VeADK 相关的功能。
Teams using veadk-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/veadk-skills/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How veadk-skills Compares
| Feature / Agent | veadk-skills | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
根据用户的功能需求，完成与 VeADK 相关的功能。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# VeADK Agent 生成 本技能可以根据用户的需求，生成符合要求的 VeADK Agent 代码，或完成 VeADK 相关功能。 ## 触发条件 1. 用户简要描述了其功能需求，并希望构建一个 Agent 来完成； 2. 用户希望可以将已有的 Langchain/Langgraph 代码转化为 VeADK Agent 代码 3. 用户希望可以将已有的 Dify 工作流转化为 VeADK Agent 代码 ## 具体步骤 下面是本技能不同的组件能力。 ### 直接根据需求生成 Agent 请你遵循以下步骤： 1. 分析用户需求，生成对应的 Agent 系统结构，参考 `references/generator/analyze.md` 2. 提示词优化，参考 `references/generator/refine_prompt.md` 3. 生成 Agent 代码，参考 `references/generator/coding.md` ### Langchain 代码转换为 VeADK Agent 请你遵循以下步骤： 1. 分析原有 Langchain 或 Langgraph 代码 2. 将原有代码改为 VeADK Agent，对应关系详见 `references/converter/langchain_rules.md` 3. 参照 `references/common/` 目录内的文档来生成 VeADK 代码 ### Dify 工作流转换为 VeADK Agent 请你遵循以下步骤： 1. 分析原有 Dify 工作流 DSL（一般为一个 Yaml 格式文件） 2. 将原有代码改为 VeADK Agent，对应关系详见 `references/converter/dify_rules.md` 3. 参照 `references/common/` 目录内的文档来生成 VeADK 代码 ## 后续工作 在完成 Agent 代码编写后，调用脚本保存代码产物： - `agent_name/__init__.py`: 固定内容为 `from . import agent # noqa` - `agent_name/agent.py`：包含所有智能体的代码 其中，`agent_name` 是你认为合适的 Agent 的名称。 脚本调用方法为： ```bash python save_file.py --path ... --content ... ```
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