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 pangzhenying2025/hermes-automotive-skills --skill china-behavioral-safetygit clone --depth 1 https://github.com/pangzhenying2025/hermes-automotive-skillsWrote 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/pangzhenying2025/hermes-automotive-skills/china-behavioral-safety)<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/china-behavioral-safety"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/china-behavioral-safety/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/pangzhenying2025/hermes-automotive-skills/china-behavioral-safety"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/china-behavioral-safety.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 | $0.00029 | $0.00857 |
| Opus 5 | $0.00015 | $0.00428 |
| Sonnet 5 | $0.00006 | $0.00171 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
china-behavioral-safety 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 9d 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
Behavioral Safety — China Standard
IEEE 2846-2022 自动驾驶系统安全假设
标准信息
| 属性 | 值 |
|---|---|
| 标准编号 | IEEE 2846-2022 |
| 名称 | A Framework for ADS Safety Assumptions |
| 状态 | 已发布(2022年) |
| 推荐等级 | P1-强烈推荐 |
| 核心内容 | 定义ADS行为安全模型,含RSS(Responsibility-Sensitive Safety)框架 |
核心概念
安全假设框架
IEEE 2846 安全假设体系
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. 合理预见行为 (Reasonably Foreseeable Behavior)
└── 其他道路参与者的预期行为范围
2. 安全响应规则 (Safety Response Rules)
└── ADS在各场景下的安全行为要求
3. 事故责任判定 (Blame Attribution)
└── 当碰撞不可避免时的责任归属
4. 安全距离模型 (Safe Distance Model)
├── 纵向安全距离 = f(v_ego, v_front, a_max_brake, reaction_time)
├── 横向安全距离 = f(v_lateral, lane_width)
└── 交叉路口安全模型
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
RSS安全距离模型
# RSS纵向安全距离计算
def rss_longitudinal_safe_distance(
v_ego: float, # 自车速度 (m/s)
v_front: float, # 前车速度 (m/s)
rho: float, # 反应时间 (s), 通常取0.5-1.0s
a_max_accel: float, # 最大加速度 (m/s²)
a_max_brake: float, # 最大制动减速度 (m/s²)
a_min_brake: float, # 前车最小制动减速度 (m/s²)
) -> float:
"""
d_safe = v_ego * rho + 0.5 * a_max_accel * rho²
+ (v_ego + rho * a_max_accel)² / (2 * a_max_brake)
- v_front² / (2 * a_min_brake)
"""
v_ego_after_reaction = v_ego + rho * a_max_accel
d_ego_reaction = v_ego * rho + 0.5 * a_max_accel * rho**2
d_ego_brake = v_ego_after_reaction**2 / (2 * a_max_brake)
d_front_brake = v_front**2 / (2 * a_min_brake)
return max(0, d_ego_reaction + d_ego_brake - d_front_brake)
中国场景适配
IEEE 2846 中国场景适配考虑
├── 反应时间参数:需考虑中国交通密度
├── 行为假设:电动自行车/三轮车行为模型
├── 交叉路口:中国特有交通规则(右转不停车等)
├── 高速公路:匝道合流行为差异
└── 责任判定:与中国交通法规对齐
相关技能
skills/china-standards/ads-safety/— ADS安全要求skills/china-standards/ai-safety/— AI安全标准skills/automotive-e2e-safety-analysis/— 端到端安全分析
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.
- 9d ago First seen · 85 lines · 29 tokens per session scan A 18dc1f852bc7
china-behavioral-safety is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 857 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 2026-09-03.
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