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 automotive-china-parking-compliancegit 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/automotive-china-parking-compliance)<a href="https://agentmods.dev/skills/pangzhenying2025/hermes-automotive-skills/automotive-china-parking-compliance"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-china-parking-compliance/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/automotive-china-parking-compliance"><img src="https://agentmods.dev/badge/skills/pangzhenying2025/hermes-automotive-skills/automotive-china-parking-compliance.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 | $0.00025 | $0.02848 |
| Opus 5 | $0.00013 | $0.01424 |
| Sonnet 5 | $0.00005 | $0.00570 |
| Haiku 4.5 | $0.00003 | $0.00285 |
Grade A, and why
automotive-china-parking-compliance 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 12d 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automotive China Parking Compliance
China Parking Compliance
China Parking System Compliance — Parking Assistance & Automated Parking Standards
Overview
Expert guidance for compliance with China's standards for parking assistance and automated parking systems, including APA (Automatic Parking Assist), RPA (Remote Parking Assist), AVP (Automated Valet Parking), and HPA (Home-zone Parking Assist). Covers both mandatory and recommended national standards.
Standard Hierarchy
中国泊车标准体系
├── 强制性国标
│ ├── GB — 泊车辅助系统性能要求与试验方法
│ └── GB — 遥控泊车辅助系统技术要求
├── 推荐性国标
│ ├── GB/T — 自动泊车系统性能要求与试验方法
│ ├── GB/T — 自动代客泊车系统技术要求
│ ├── GB/T — 泊车功能安全要求
│ └── GB/T — 泊车预期功能安全要求
├── 行业标准
│ ├── QC/T — 泊车辅助超声波传感器技术要求
│ └── QC/T — 全景影像系统技术要求
└── 团体标准
├── T/CSAE — 智能泊车系统分级
└── T/CSAE — 记忆泊车系统技术要求
Parking Function Classification
Function Levels
泊车功能分级(参考T/CSAE标准)
─────────────────────────────────────────────────────
Level 0: 泊车预警
└── 超声波/摄像头障碍物提醒(无自动控制)
Level 1: 半自动泊车辅助(APA-S)
└── 系统控制转向,驾驶员控制油门/制动/换挡
Level 2: 自动泊车辅助(APA)
└── 系统控制转向+制动+油门,驾驶员监控
└── 驾驶员在车内,脚在制动踏板附近
Level 3: 遥控泊车辅助(RPA)
└── 驾驶员在车外,通过手机/钥匙遥控
└── 低速(<5km/h),短距离(<6m通常)
Level 4: 记忆泊车(HPA)
└── 学习固定路线,自动泊入/泊出
└── 驾驶员可在车外,通过App监控
Level 5: 自动代客泊车(AVP)
└── 车辆自主寻找车位并泊车
└── 需要场端基础设施配合(L4级别)
─────────────────────────────────────────────────────
Parking Scenario Types
parking_scenarios = {
"平行泊车(侧方位)": {
"车位尺寸": "车长+1.2m × 车宽+0.8m (最小)",
"速度限制": "<10 km/h",
"检测距离": ">15m前方探测",
},
"垂直泊车": {
"车位尺寸": "车宽+0.8m × 5.0m (最小)",
"速度限制": "<5 km/h",
"接近角度": "90° ± 15°",
},
"斜向泊车": {
"车位尺寸": "按角度计算",
"角度": "30°/45°/60°",
"速度限制": "<5 km/h",
},
"遥控泊车": {
"遥控距离": "<6m",
"速度限制": "<5 km/h (前进), <3 km/h (倒车)",
"紧急制动": "松开遥控按键即停",
},
"记忆泊车(HPA)": {
"学习路径长度": "<500m",
"速度限制": "<15 km/h",
"路径偏差容忍": "<0.3m",
},
"代客泊车(AVP)": {
"运行范围": "指定停车场/区域",
"速度限制": "<20 km/h",
"场端配合": "需要V2X/高精地图",
},
}
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.
- 12d ago First seen · 274 lines · 25 tokens per session scan A aa13b806c0fb
automotive-china-parking-compliance is a skill published in the GitHub repository pangzhenying2025/hermes-automotive-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 2,848 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 2026-08-31.
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