Best use case
OpenViking Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
OpenViking 上下文数据库集成 — 给 AI 朝廷加上长期记忆和知识库。
Teams using OpenViking Skill 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/openviking/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How OpenViking Skill Compares
| Feature / Agent | OpenViking Skill | 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?
OpenViking 上下文数据库集成 — 给 AI 朝廷加上长期记忆和知识库。
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
# OpenViking Skill
OpenViking 上下文数据库集成 — 给 AI 朝廷加上长期记忆和知识库。
## 什么是 OpenViking
OpenViking 是火山引擎开源的 AI Agent 上下文数据库，用文件系统范式统一管理记忆、资源和技能。
相比 OpenClaw 默认的 qmd 记忆后端，OpenViking 在大规模文档场景下更强：
| 能力 | qmd（默认） | OpenViking |
|------|-----------|------------|
| 语义搜索 | 基础向量匹配 | 目录递归 + 语义融合 |
| 自动摘要 | ❌ | ✅ L0/L1/L2 三层 |
| 结构化浏览 | ❌ | ✅ 虚拟文件系统 |
| Token 节省 | ❌ | ✅ 按需加载 |
## 安装
### 1. 安装 Python 包
```bash
pip install openviking
```
### 2. 获取 Embedding API Key
推荐使用免费的 NVIDIA NIM API：
1. 访问 https://build.nvidia.com/
2. 登录 → API Keys → 生成 Key
3. 保存 key（以 `nvapi-` 开头）
也可以用火山引擎、OpenAI 等其他 provider。
### 3. 创建配置文件
```bash
mkdir -p ~/.openviking
cat > ~/.openviking/ov.conf << 'EOF'
{
"embedding": {
"dense": {
"api_base": "https://integrate.api.nvidia.com/v1",
"api_key": "YOUR_NVIDIA_API_KEY",
"provider": "openai",
"dimension": 4096,
"model": "nvidia/nv-embed-v1"
}
},
"vlm": {
"api_base": "https://integrate.api.nvidia.com/v1",
"api_key": "YOUR_NVIDIA_API_KEY",
"provider": "openai",
"model": "meta/llama-3.3-70b-instruct"
}
}
EOF
```
### 4. 设置环境变量
```bash
echo 'export OPENVIKING_CONFIG_FILE=~/.openviking/ov.conf' >> ~/.bashrc
source ~/.bashrc
```
## 使用方式
Agent 通过 exec 调用 `scripts/viking.sh` 脚本：
```bash
# 查看状态
bash skills/openviking/scripts/viking.sh info
# 索引文件
bash skills/openviking/scripts/viking.sh add ./my-document.md
# 批量索引目录
bash skills/openviking/scripts/viking.sh add-dir ./docs/
# 语义搜索
bash skills/openviking/scripts/viking.sh search "某个话题"
# 浏览已索引的文件
bash skills/openviking/scripts/viking.sh list
# 读取文件摘要
bash skills/openviking/scripts/viking.sh summary <file-path>
```
## 朝廷集成建议
- **兵部**：索引代码仓库，搜索相关代码片段
- **户部**：索引财务报表，查询历史数据
- **礼部**：索引品牌素材和营销案例
- **工部**：索引运维文档和 runbook
- **刑部**：索引法律法规和合同模板
建议保留 qmd 做日常轻量记忆，OpenViking 做大规模知识库。Related Skills
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