danghuangshang is a multi-agent collaboration system that organizes specialized AI agents into a hierarchy modeled on historical Chinese government institutions. Users delegate tasks to these agents through platforms such as Discord or Feishu, with roles for coordination, coding, review, memory, and automation. Its catalogue entries are the project's agents and skills.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wanikua/danghuangshangnpx agentmods add skills/wanikua/danghuangshang/openvikingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wanikua/danghuangshang/openviking)<a href="https://agentmods.dev/skills/wanikua/danghuangshang/openviking"><img src="https://agentmods.dev/badge/skills/wanikua/danghuangshang/openviking/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wanikua/danghuangshang/openviking"><img src="https://agentmods.dev/badge/skills/wanikua/danghuangshang/openviking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 68 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- medium Rogue Agent · line 43 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.00777 |
| Opus 5 | $0.00010 | $0.00388 |
| Sonnet 5 | $0.00004 | $0.00155 |
| Haiku 4.5 | $0.00002 | $0.00078 |
Grade A, and why
openviking scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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
pip install openviking
2. 获取 Embedding API Key
推荐使用免费的 NVIDIA NIM API：
- 访问 https://build.nvidia.com/
- 登录 → API Keys → 生成 Key
- 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
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
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：
# 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。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 105 lines · 19 tokens per session scan A 95532e241363
openviking is a skill published in the GitHub repository wanikua/danghuangshang (2,700 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 777 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
setup-discord-multibot
Configure or extend a multi-bot Discord setup for Claude Code, where each project directory is bridged to its own dedicated Discord bot. Use when the user wants to (a) add a new Discord bot for a new project, (b) initially set up the per-project Discord architecture, (c) pair a bot when the official /discord:access…
agent-browser
Web search and browser automation using websearch, webfetch, and webbrowser tools. Use when: internet lookup, latest/real-time information, cross-source verification, any URL mentioned by user, dynamic page interaction, web crawling, site analysis, news search, price check, documentation lookup. Do NOT use for local…
memory
Two-layer persistent memory system (longterm facts + daily recall) backed by memory.db. Use when the user mentions remembering, recalling past events, storing preferences, or asks about past context. Also use automatically to persist important user preferences, project facts, and relationship data. Do NOT use for…
browserwing-admin
Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.
commonly
You are a member of a Commonly workspace — a shared space where humans and AI agents from any origin collaborate in pods (chat rooms with memory). Use this whenever you are connected to Commonly via the commonly MCP tools: to read what's happening, post, remember things across sessions, react, DM other agents, and…
dingtalk_channel_connect
A browser-based setup guide for connecting a MateClaw assistant to DingTalk, a Chinese workplace messaging platform. It creates and configures a DingTalk application, then publishes the configuration.