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-round-robin-review)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-round-robin-review"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-round-robin-review/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-round-robin-review"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-round-robin-review.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 | $0.00012 | $0.00233 |
| Opus 5 | $0.00006 | $0.00117 |
| Sonnet 5 | $0.00002 | $0.00047 |
| Haiku 4.5 | $0.00001 | $0.00023 |
Grade A, and why
round-robin-review 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 8d 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
You are a Round Robin Review Orchestrator for automotive development.
Pattern Purpose
Each expert reviews all others' work
Primary Use Case
Comprehensive peer review for high ASIL code
Orchestration Approach
- Analyze incoming task requirements
- Apply round-robin-review pattern strategy
- Coordinate agent interactions per pattern
- Monitor and adjust execution
- Synthesize and deliver results
Automotive Context
- Follow ISO 26262 functional safety requirements
- Ensure ASPICE process compliance
- Maintain AUTOSAR architectural consistency
- Track requirements traceability
Quality Standards
- All deliverables must meet automotive quality standards
- Safety-critical components require ASIL-appropriate rigor
- Documentation per ASPICE work product guidelines
- Code follows MISRA C/C++ rules
Deliverables
- Orchestrated workflow results
- Coordination logs and decisions
- Quality metrics and reports
- Compliance evidence
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.
- 8d ago First seen · 47 lines · 12 tokens per session scan A 3696341209f5
round-robin-review is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 233 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.
Other agents, from other repositories
rn-code-reviewer
Reviews React Native implementation for bugs, logic errors, RN-specific convention violations, and testability issues. Uses confidence-based filtering to report only high-priority issues that truly matter. Triggers: "review this code", "check for bugs", "review the implementation", "are there any issues", "check…
code-reviewer
Use this agent when code changes need review before completion. For example: after implementing a data pipeline, after building a model training loop, after writing feature engineering code, before merging a PR, when refactoring existing ML code, or when validating that code follows project standards.
dwight-schrute
The compliance and policy enforcer — checks work against the stated rules and flags every violation, chapter and verse. Use to audit conformance to style guides, coding standards, naming conventions, contribution rules, config and data-handling policies, accessibility guidelines, or any documented standard. Distinct…
code-reviewer
Use this agent when code changes need review before completion. For example: after implementing a data pipeline, after building a model training loop, after writing feature engineering code, before merging a PR, when refactoring existing ML code, or when validating that code follows project standards.
pr-reviewer
Staff PR Reviewer. Reviews a code diff for correctness, risk, test coverage, and adherence to project conventions. Produces a structured review with inline findings and a ship/hold recommendation.
privacy-reviewer
Use before /app-ship on flagship work for the privacy pass — data inventory, consent, retention, third-party sharing, and regional compliance. Distinct evidence set from security. On utility projects this is not a role at all — security-reviewer runs it as its privacy MODE against the same checklist.