china-scenario-safety

china-scenario-safety is a skill for Claude Code, Codex from pangzhenying2025/hermes-automotive-skills. It costs 41 tokens per session (1,105 once invoked), scanned A, original, MIT.

A guide to assessing the safety of automated-driving systems using Chinese and international standards. It describes how to define, parameterize, select, execute, and review driving scenarios.

In plain words
What is it for?
Use it to organize simulation, closed-track, and road tests, prioritize scenarios by risk, analyze coverage, and support safety arguments.
Why use it?
It gives safety teams a structured way to turn real-world risks, accidents, regulations, and expert knowledge into testable scenarios.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to organize simulation, closed-track, and road tests, prioritize scenarios by risk, analyze coverage, and support safety arguments.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pangzhenying2025/hermes-automotive-skills/china-scenario-safety
Install

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.

Any agent
npx skills add pangzhenying2025/hermes-automotive-skills --skill china-scenario-safety
Clone the repo
git clone --depth 1 https://github.com/pangzhenying2025/hermes-automotive-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for china-scenario-safety

README.md
[![agentmods](https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/china-scenario-safety/github.svg)](https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/china-scenario-safety)
Your own site
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agentmods 80×15 button for china-scenario-safety

Your own site · 80×15
<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/china-scenario-safety"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/china-scenario-safety.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,105 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.01105
Opus 5 $0.00020 $0.00553
Sonnet 5 $0.00008 $0.00221
Haiku 4.5 $0.00004 $0.00111

Measured 9d ago against content hash 61ed90eb27e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

china-scenario-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.

skills/china-scenario-safety/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scenario Safety — China Standard

场景安全评估框架 — ISO 34501/34502 + ISO 34503/34504/34505

标准集一览

标准编号 名称 状态 推荐等级
ISO 34501:2022 自动驾驶系统测试场景 术语 已发布 P1
ISO 34502:2022 基于场景的安全评估框架 已发布 P1
ISO 34502 GB征求意见稿 基于场景的安全评估框架(中国版) 征求意见稿 P3
ISO 34503/34504/34505 场景描述/分类/生成方法 DIS阶段 P3

ISO 34502:2022 基于场景的安全评估工程框架

核心概念

场景安全评估三层模型
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Functional Scenario (功能场景)
  └── 自然语言描述的抽象场景
  └── 例:"高速公路上前车突然变道,暴露前方静止车辆"

Logical Scenario (逻辑场景)
  └── 参数化描述,参数取值为范围/分布
  └── 例:ego_speed ∈ [100,120] km/h,
          target_speed = 0 km/h,
          cut_out_ttc ∈ [2.0, 5.0] s

Concrete Scenario (具体场景)
  └── 所有参数赋具体值的可执行场景
  └── 例:ego_speed = 110 km/h,
          target_speed = 0 km/h,
          cut_out_ttc = 3.2 s
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

安全评估流程

ISO 34502 安全评估流程
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Phase 1: 场景识别
  ├── 从标准/法规提取
  ├── 从事故数据提取
  ├── 从自然驾驶数据提取
  └── 专家知识补充

Phase 2: 场景描述与参数化
  ├── 功能场景定义
  ├── 逻辑场景参数化
  └── 参数空间定义

Phase 3: 场景选择
  ├── 基于风险的优先级排序
  ├── 覆盖度分析
  └── 测试资源分配

Phase 4: 场景执行
  ├── 仿真测试(批量执行)
  ├── 封闭场地测试(关键场景)
  └── 开放道路测试(真实环境)

Phase 5: 安全论证
  ├── 通过率统计
  ├── 覆盖度论证
  ├── 残余风险评估
  └── 安全案例构建
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

与DFM框架的关联

ISO 34502 ↔ DFM关联
├── ISO 34502定义了场景安全评估的工程框架
├── DFM(驾驶员基础模型)提供:
│   ├── 人类驾驶行为基线(作为安全参考)
│   ├── 场景暴露频率(基于大规模NDD)
│   ├── 场景参数分布(基于7.5M+轨迹数据)
│   └── 场景批评性量化指标
└── 组合使用:DFM为ISO 34502提供数据驱动的场景选择和安全论证

ISO 34503/34504/34505 场景标准族(P3)

ISO 3450x 场景标准族
├── ISO 34503: Specification of Operational Design Domain
│   └── ODD描述方法和分类框架
├── ISO 34504: Scenario Categorization
│   └── 场景分类方法(基于抽象层次)
└── ISO 34505: Scenario Generation and Selection
    └── 场景生成和选择方法

相关技能

  • skills/china-standards/sotif/ — SOTIF标准集
  • skills/china-standards/odd/ — ODD标准
  • skills/automotive-scenario-driven-testing/ — 场景驱动测试方法
  • skills/automotive-dfm-benchmarking/ — DFM基准评测

Read the full file on GitHub · 113 lines

Changes

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.

  1. 9d ago First seen · 113 lines · 41 tokens per session scan A 61ed90eb27e8

Subscribe to this mod's changes

china-scenario-safety is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,105 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 2026-09-03.

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