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 AutoZYX-Labs/ADSafetyPilot --skill china-regulatorygit clone --depth 1 https://github.com/AutoZYX-Labs/ADSafetyPilotWrote 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/autozyx-labs/adsafetypilot/china-regulatory)<a href="https://agentmods.dev/skills/autozyx-labs/adsafetypilot/china-regulatory"><img src="https://agentmods.dev/badge/skills/autozyx-labs/adsafetypilot/china-regulatory/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/autozyx-labs/adsafetypilot/china-regulatory"><img src="https://agentmods.dev/badge/skills/autozyx-labs/adsafetypilot/china-regulatory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00032 | $0.00659 |
| Opus 5 | $0.00016 | $0.00329 |
| Sonnet 5 | $0.00006 | $0.00132 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
china-regulatory 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 10d 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
中国标准法规 | China Regulatory Intelligence
本技能覆盖中国智能网联汽车全标准体系，聚焦安全相关强制标准。
强制性国标 (GB)
L2 组合驾驶辅助系统安全要求
- 状态：公开征求意见（2024年9月版）
- 覆盖功能：ACC、AEB、LKA、LDW、BSW、RCTA等
- 核心要求：功能安全+预期功能安全双重要求
- 测试场景：全部对标收录于本项目场景库
GB 44495 自动驾驶系统安全要求 (L3)
- 状态：制定中
- 覆盖：有条件自动驾驶（L3）的安全技术要求
- 关键要求：最小风险策略(MRC)、驾驶员接管(TOR)、ODD定义
GB 44496 自动泊车系统技术要求
- 状态：制定中
- 覆盖：垂直泊车、侧方泊车、斜向泊车、记忆泊车
推荐性国标 (GB/T)
| 标准号 | 名称 | 领域 |
|---|---|---|
| GB/T 43267-2023 | 道路车辆 预期功能安全 | SOTIF（对标ISO 21448） |
| GB/T 40429 | 汽车驾驶自动化分级 | 分级（对标SAE J3016） |
| GB/T 41798 | 自动驾驶功能场景分类 | 场景分类 |
| GB/T 41799 | 自动驾驶系统设计运行条件 | ODD定义 |
| GB/T 40857 | 汽车网络安全管理体系 | 网络安全（对标ISO 21434） |
| GB/T 39901 | 乘用车AEBS性能要求 | AEB测试 |
中国特有场景与实践
交通场景特殊性
- 非机动车混行（电动自行车、三轮车）
- 高密度加塞（城市拥堵路段）
- 施工区管理差异（临时标线、人工指挥）
- 非标信号控制（部分城市路口）
- 高速公路应急车道使用差异
开发流程实践
- C-NCAP / C-IASI 集成
- 中国ASPICE实践
- 国产工具链适配（51Sim等仿真平台）
使用示例
用户：我的L2 ACC+LKA系统需要满足中国强标，做合规性检查
输出：
1. 适用标准清单（强标+推荐标准）
2. 逐项合规差距分析
3. 必须覆盖的测试场景清单
4. 时间表建议（标准实施日期对标）
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.
- 10d ago First seen · 63 lines · 32 tokens per session scan A 6c5010230298
china-regulatory is a skill published in the GitHub repository AutoZYX-Labs/ADSafetyPilot (2 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 659 once invoked, about $0.0002 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 2026-08-31.
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