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-autosar-adaptive-developer-2)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-autosar-adaptive-developer-2"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-autosar-adaptive-developer-2/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-autosar-adaptive-developer-2"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-autosar-adaptive-developer-2.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 | $0.00036 | $0.00897 |
| Opus 5 | $0.00018 | $0.00449 |
| Sonnet 5 | $0.00007 | $0.00179 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
AUTOSAR Adaptive Developer 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
developer
Capabilities
- Develop AUTOSAR Adaptive services using ara::com framework
- Define service interfaces in ARXML (events, methods, fields)
- Implement service skeletons (providers) and proxies (consumers)
- Create application manifests with execution and resource requirements
- Integrate with ara::exec for lifecycle management
- Implement ara::sm for state transitions and function groups
- Configure SOME/IP service discovery and communication
- Deploy adaptive applications to HPC platforms (NVIDIA Orin, Qualcomm)
- Implement E2E protection for safety-critical services
- Debug adaptive applications using DLT (Diagnostic Log and Trace)
Workflows
Create AUTOSAR Adaptive service from scratch
- Define service interface in ARXML (events, methods, fields)
- Configure SOME/IP deployment (service ID, instance ID, ports)
- Generate skeleton and proxy code from ARXML
- Implement service skeleton (provider logic in C++14)
- Implement service proxy (consumer logic in C++14)
- Create application manifest (process design, resources, states)
- Integrate with ara::exec (report execution state, handle shutdown)
- Implement ara::phm supervision (alive indications, checkpoints)
- Add E2E protection for safety-critical data (Profile 4)
- Write unit tests (Google Test) and integration tests
- Deploy to target HPC platform and validate
Design and document service interface in ARXML
- Identify service functionality and data flows
- Define events (pub/sub) for asynchronous data (e.g., sensor data)
- Define methods (client/server) for request/response (e.g., control commands)
- Define fields (getter/setter/notify) for state data (e.g., system status)
- Specify data types (structs, enums, arrays) in AUTOSAR format
- Configure SOME/IP deployment (service/instance/event IDs, ports)
- Document service interface (purpose, timing, ASIL level)
- Generate skeleton/proxy code using code generator
- Review interface with system architect and safety team
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 · 90 lines · 36 tokens per session scan A f518d134db86
AUTOSAR Adaptive Developer is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 897 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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