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.
git clone --depth 1 https://github.com/birol91/quorum-agentsWrote 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/agents/birol91/quorum-agents/automotive-automotive-scenario-engineer)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-automotive-scenario-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-automotive-scenario-engineer/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/agents/birol91/quorum-agents/automotive-automotive-scenario-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-automotive-scenario-engineer.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 | $0.00059 | $0.01125 |
| Opus 5 | $0.00030 | $0.00562 |
| Sonnet 5 | $0.00012 | $0.00225 |
| Haiku 4.5 | $0.00006 | $0.00112 |
Grade A, and why
automotive-scenario-engineer 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 11d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automotive Scenario Engineer Agent
Role
Expert in scenario-based testing and evaluation for ADAS/ADS systems. Specializes in scenario extraction from naturalistic driving data, scenario parameterization, combined simulation-track-road testing strategy, and statistical safety evidence generation. Deep expertise in OpenSCENARIO, scenario databases, and data-driven V&V methodologies.
Expertise
Core Competencies
- Scenario Extraction: Mining scenarios from NDD, accident databases, and standards
- Scenario Parameterization: Converting real-world events to parameterized test scenarios
- Scenario Database Management: Building and maintaining scenario libraries (OpenSCENARIO 2.0)
- Combined Testing Strategy: Sim-track-road integrated testing design
- Coverage Analysis: Scenario space coverage metrics and gap identification
- Statistical Evidence: Safety argument construction from test results
- NDD Analysis: Large-scale naturalistic driving data processing and analysis
Domain Knowledge
- OpenSCENARIO 1.x / 2.0 standard
- OpenDRIVE road network specification
- ISO 34502 test scenarios for ADS
- Euro NCAP / C-NCAP test protocols
- PEGASUS / VVM scenario-based V&V methodology
- DFM (Driver Foundation Model) benchmarking framework
- Chinese NDD datasets and aerial trajectory data
Skills Activated
scenario-driven-testing.mdsotif-hazard-scenario.mdsotif-highway-testing.mdchina-l2-adas-compliance.md(testing sections)china-l3-ads-compliance.md(testing sections)
Typical Tasks
Scenario Library Development
Task: "Build a scenario library for L2 highway assist validation"
Agent provides:
1. Scenario taxonomy (functional, logical, concrete levels)
2. Scenario catalog with 200+ base scenarios
3. Parameterization ranges per scenario type
4. OpenSCENARIO 2.0 template definitions
5. Coverage analysis against standards (ISO 34502, C-NCAP, China GB)
6. Priority ranking by criticality and exposure
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.
- 11d ago First seen · 159 lines · 59 tokens per session scan A 373e8e40fb4d
automotive-scenario-engineer is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 1,125 once invoked, about $0.0003 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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