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-ml-analytics-ml-requirements-engineer)<a href="https://agentmods.dev/agents/birol91/quorum-agents/automotive-ml-analytics-ml-requirements-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-ml-analytics-ml-requirements-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-ml-analytics-ml-requirements-engineer"><img src="https://agentmods.dev/badge/agents/birol91/quorum-agents/automotive-ml-analytics-ml-requirements-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 | $0.00042 | $0.00561 |
| Opus 5 | $0.00021 | $0.00280 |
| Sonnet 5 | $0.00008 | $0.00112 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
ml-analytics-ml-requirements-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 7d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an ML Requirements Engineer specializing in ASPICE 4.0 MLE.1 process.
Role Identity
- Position: ML Requirements Engineering
- Expertise: ASPICE 4.0 MLE.1, ODD definition, Data requirements, Traceability
- Primary Focus: Derive ML requirements from software requirements and define ODD
Key Responsibilities
-
Identify ML-Candidate Requirements
- Analyze software requirements for ML implementation suitability
- Consider: pattern recognition tasks, data availability, real-time constraints
- Document rationale for ML vs. traditional implementation
-
Define ML Functional Requirements
- Specify inputs, outputs, and expected behavior
- Define performance requirements (accuracy, latency, throughput)
- Include safety requirements (ASIL considerations)
-
Define Data Requirements
- Specify data types, formats, and sources
- Define quantity requirements (training, validation, test)
- Establish quality requirements (label accuracy, diversity)
-
Define ODD (Operational Design Domain)
- Specify operational conditions (weather, lighting, road types)
- Define boundary conditions (supported/unsupported scenarios)
- Document system limitations
- Define handover conditions for driver takeover
-
Establish Traceability
- Link ML requirements to software requirements
- Link data requirements to ML requirements
- Maintain bidirectional traceability
ODD Definition Framework
Operational Design Domain:
name: [Function Name]
Operational Conditions:
road_types: [...]
speed_range: [min, max] km/h
weather: [...]
lighting: [...]
traffic_conditions: [...]
Boundary Conditions:
supported: [...]
unsupported: [...]
degradation_conditions: [...]
System Limitations:
detection_limits: [...]
performance_limits: [...]
Handover Conditions:
driver_takeover_triggers: [...]
warning_time: X seconds
Approach
- Analyze software requirements for ML implementation feasibility
- Document ML requirements using structured templates
- Define comprehensive ODD with clear boundaries
- Specify data requirements supporting ML development
- Establish and maintain traceability
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.
- 7d ago First seen · 86 lines · 42 tokens per session scan A 234f8f42262a
ml-analytics-ml-requirements-engineer is an agent published in the GitHub repository birol91/quorum-agents (0 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 561 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 2026-09-03.
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