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 agentmods add skills/autozyx-labs/adsafetypilot/safety-trinitynpx skills add AutoZYX-Labs/ADSafetyPilot --skill safety-trinitygit 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/safety-trinity)<a href="https://agentmods.dev/skills/autozyx-labs/adsafetypilot/safety-trinity"><img src="https://agentmods.dev/badge/skills/autozyx-labs/adsafetypilot/safety-trinity.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.00871 |
| Opus 5 | $0.00024 | $0.00436 |
| Sonnet 5 | $0.00010 | $0.00174 |
| Haiku 4.5 | $0.00005 | $0.00087 |
Grade A, and why
safety-trinity 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 6d 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
安全三支柱 | Safety Trinity
本技能打破FuSa/SOTIF/CyberSec三个标准的独立分析壁垒，提供交叉映射的统一分析流程。
为什么需要三合一？
传统做法：三个团队各做各的分析，最后开一个接口会议"对齐"。 问题：
- HARA识别的hazard可能被SOTIF触发条件放大
- TARA识别的攻击路径可能导致SOTIF功能不足
- 三个分析之间的交互效应被遗漏
交叉映射框架
FuSa HARA SOTIF触发条件 CyberSec TARA
(系统故障→危害) (功能不足→危害) (攻击→危害)
│ │ │
└──────────┬─────────────────┘─────────────────────────┘
│
┌──────────┴──────────┐
│ Unified Hazard │
│ 统一危害分析 │
│ │
│ Hazard H-001: │
│ ├─ FuSa: 雷达故障 │
│ ├─ SOTIF: 雨雾漏检 │
│ └─ Cyber: 雷达欺骗 │
│ │
│ → 统一安全目标 │
│ → 统一验证策略 │
└─────────────────────┘
分析流程
Step 1: 统一危害识别
- FuSa: 对每个功能做HARA（严重度S×暴露度E×可控性C → ASIL）
- SOTIF: 对每个功能做触发条件分析（感知局限×算法不足×人因误用）
- CyberSec: 对每个功能做TARA（资产→威胁→攻击路径→影响）
- 交叉：检查三者识别的危害是否有重叠/放大效应
Step 2: 统一安全目标
- 将三个来源的危害映射到统一的安全目标集合
- 标注每个安全目标的来源（FuSa/SOTIF/Cyber/Multiple）
- 优先处理多来源危害（更高风险）
Step 3: 统一安全需求
- 功能安全需求（TSR/HSR）
- SOTIF安全需求（场景覆盖+残余风险可接受）
- 网络安全需求（安全机制+监测+响应）
- 交叉需求：如"雷达欺骗检测"同时满足Cyber+SOTIF
Step 4: 统一验证矩阵
- 测试场景同时覆盖FuSa故障注入 + SOTIF触发条件 + Cyber攻击场景
- 避免三套测试各跑一遍的资源浪费
使用示例
用户：我的AEB系统需要做完整的安全分析
输出：
1. 统一HARA表（含FuSa/SOTIF/Cyber三列来源标注）
2. 交叉危害清单（三个领域相互放大的危害）
3. 统一安全需求分解
4. 统一验证计划（合并三类测试场景）
参考标准
- ISO 26262:2018 Road vehicles — Functional safety
- ISO 21448:2022 Road vehicles — Safety of the intended functionality
- ISO/SAE 21434:2021 Road vehicles — Cybersecurity engineering
- ISO/TR 4804:2020 Safety and cybersecurity for automated driving systems
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.
- 6d ago First seen · 80 lines · 48 tokens per session scan A 51a3003e57e6
safety-trinity is a skill published in the GitHub repository AutoZYX-Labs/ADSafetyPilot (2 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 871 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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