GOD is a control room for observing and directing societies of language-model agents running in simulated worlds. It lets researchers inspect replays, question individual agents, alter future events, reset simulations, and export experiments for reuse. The catalogue entries are skills and agents for operating and investigating these simulations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add XiaoLuoLYG/GOD --skill openjiuwen-deepsearchgit clone --depth 1 https://github.com/XiaoLuoLYG/GODWrote 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/xiaoluolyg/god/openjiuwen-deepsearch)<a href="https://agentmods.dev/skills/xiaoluolyg/god/openjiuwen-deepsearch"><img src="https://agentmods.dev/badge/skills/xiaoluolyg/god/openjiuwen-deepsearch/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/xiaoluolyg/god/openjiuwen-deepsearch"><img src="https://agentmods.dev/badge/skills/xiaoluolyg/god/openjiuwen-deepsearch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00098 | $0.01206 |
| Opus 5 | $0.00049 | $0.00603 |
| Sonnet 5 | $0.00020 | $0.00241 |
| Haiku 4.5 | $0.00010 | $0.00121 |
Grade A, and why
openJiuwen-DeepSearch 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
openJiuwen-DeepSearch 技能使用指南
- 每次使用该技能之前都先完整阅读一遍SKILL.md学习技能
- 无需配置环境
- 切换到openJiuwen-DeepSearch技能文件夹路径
- 在该路径下直接运行
uv run "scripts\main.py" --mode query --query "研究报告标题"命令即可，不需要uv sync等操作。 - 执行命令后会启动子进程在后台执行，请确保后台子进程正常运行，你需要给出openJiuwen-DeepSearch技能文件夹绝对路径作为报告输出目录并提示用户等待约15分钟直至报告文件输出。
- 技能执行时间约15分钟，执行完上述命令后，该程序会拉起一个后台子进程完成报告生成任务，并且在openJiuwen-DeepSearch技能文件夹绝对路径下的PID.info中会输出该子进程的PID。你必须确保后台子进程正常运行并读取PID.info中的PID，之后直接结束当前轮次对话并提示用户等待，当用户询问报告是否完成生成时，你需要通过对应子进程PID的进程任务和openJiuwen-DeepSearch技能文件夹路径中的Markdown/Doc/Html文件列表判断是否完成本次研究报告的生成。
- 你需要读取openJiuwen-DeepSearch技能文件夹下的PID.info文件来获取子进程的PID，然后创建一个定时任务（执行周期每20分钟）监测子进程的PID来定期检查对应子进程的存活状态，当子进程结束运行后，你要检查本次研究对应的报告是否生成，并通知用户结果，然后必须清理当前的定时任务，必须检查并更新当前的todo list。
执行深度研究
命令行执行（推荐）
uv run "scripts\main.py" --mode query --query "AI手机行业研究报告"
示例场景
金融分析研报
uv run "scripts\main.py" --mode query --query "美联储2025年降息对A股科技板块的影响"
学术与政策研究
uv run "scripts\main.py" --mode query --query "中国'新质生产力'政策对制造业中小企业的影响"
行业分析
uv run "scripts\main.py" --mode query --query "2025年新能源汽车行业发展趋势分析"
可选环境变量
| 变量名 | 说明 | 默认值 |
|---|---|---|
MAX_WEB_SEARCH_RESULTS |
单次搜索最大返回结果数 | 5 |
EXECUTION_METHOD |
workflow 执行方式 | parallel |
执行方式
- parallel：并行执行（默认，推荐）
- dependency_driving：依赖驱动执行
输出结果
日志输出
- 日志目录：
./output/logs/ - 结果目录：openJiuwen-DeepSearch技能文件夹根目录
报告输出
最终研究报告会以流式的方式输出到到控制台，包含：
- 查询规划结果
- 信息收集过程
- 理解分析内容
- 最终生成的报告
错误处理
常见错误
-
缺少必需的环境变量
缺少必需的环境变量: LLM_API_KEY, WEB_SEARCH_API_KEY解决方案：检查
.env文件是否正确配置 -
API Key 无效
Error: Invalid API key解决方案：检查
.env文件中的 API Key 是否正确
注意事项
- 无需配置环境：切换到在openJiuwen-DeepSearch技能文件夹路径后直接使用
uv run命令执行，该命令会使用技能文件夹根目录的.venv环境 - 查询内容：查询内容支持空格，无需额外引号
- 技能移植性：技能支持任意位置复制，无路径硬编码依赖
What ships with it
7 files 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.
- 7d ago First seen · 109 lines · 98 tokens per session scan A cbdbff2ea02b
openJiuwen-DeepSearch is a skill published in the GitHub repository XiaoLuoLYG/GOD (1,105 stars, last pushed 14d ago), licensed Apache-2.0. It adds 98 tokens to every session and 1,206 once invoked, about $0.0005 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 2026-09-03.
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