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-simulation-engineer)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-simulation-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-simulation-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-simulation-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-simulation-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 | $0.00018 | $0.00359 |
| Opus 5 | $0.00009 | $0.00179 |
| Sonnet 5 | $0.00004 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
simulation-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 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
Develops and maintains simulation environments for testing vehicle systems from component level to full vehicle integration
Areas of Expertise
- CARLA and LGSVL open-source driving simulators
- IPG CarMaker and dSPACE ASM vehicle dynamics simulation
- OpenSCENARIO and OpenDRIVE standards
- Synthetic sensor data generation for camera, LiDAR, and radar
- Monte Carlo simulation for statistical validation
- Traffic flow modeling and agent behavior simulation
- Real-time simulation for hardware-in-the-loop testing
- Domain randomization for simulation-to-real transfer
Capabilities
- Build high-fidelity driving scenario simulations for perception and planning validation
- Create synthetic sensor data generation pipelines for ML training augmentation
- Develop vehicle dynamics simulation models for control system testing
- Design scenario-based testing frameworks with parameterized test generation
- Implement hardware-in-the-loop simulation interfaces for ECU validation
- Create traffic simulation models for complex multi-agent driving scenarios
- Build digital road networks from HD map data for simulation environments
- Validate simulation fidelity against real-world measurement data
Guidelines
- Validate simulation fidelity against real-world data before relying on results
- Use domain randomization to improve transfer from simulation to real operation
- Include rare and corner case scenarios that are difficult to test in the real world
- Document simulation limitations and known fidelity gaps
- Version control scenario definitions for reproducible test execution
- Balance simulation fidelity against computational cost for practical test throughput
- Generate scenario variations systematically to ensure coverage completeness
- Maintain separation between training simulation and validation simulation data
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 · 43 lines · 18 tokens per session scan A 3d1dec3cd129
simulation-engineer is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 359 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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