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Use when reviewing, designing, or modifying Java enterprise systems that may support EU Market Abuse Regulation concerns, market surveillance, suspicious order and transaction reports, insider dealing controls, unlawful disclosure controls, market manipulation detection, inside information disclosure workflows, insider-list evidence, PDMR transaction notifications, alert explainability, model or rule provenance, reviewer decisions, or compliance escalation. This should trigger for requests such
Passed 15 of 21 test cases with the skill, and 9 of 21 without it.
and 4 more in the full report
7 fixed9 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
Our team is updating a Java-based market manipulation alert engine that uses machine learning to score suspicious quote adjustments and cross-venue trades. Please review our architecture and data lineage for regulatory alignment with EU market abuse rules. Provide a structured review report that identifies evidence gaps regarding model provenance, false-positive tracking, and alert explainability, along with specific engineering recommendations and residual risk handoffs.
| Checked | Without skill | With skill |
|---|---|---|
| States explicitly that market manipulation determinations require qualified legal owner review. | Missed | Passed |
| Identifies evidence gaps concerning machine learning model provenance. | Passed | Passed |
| Recommends explainability controls for alert triage. | Passed | Passed |
The instructions your model reads when the skill loads.
Use this Skill to review Java enterprise applications, trading systems, order-management services, transaction-monitoring pipelines, market-data platforms, surveillance services, disclosure workflows, insider-list tooling, alert triage applications, investigation records, CI/CD workflows, or operational tooling that may support Market Abuse Regulation (MAR) concerns.
Apply this Skill to determine what engineering controls, reviewable evidence, and escalation paths are needed before a system is released, connected to production trading data, used for suspicious order or transaction monitoring, used to manage inside information, or used to support market-surveillance decisions.
This Skill is not legal advice. It helps Java engineers, architects, tech leads, platform teams, market-surveillance teams, compliance engineering teams, and reviewers identify when MAR concerns may apply and how to translate market-integrity expectations into enterprise architecture controls such as suspicious order and transaction monitoring, insider dealing controls, market manipulation signals, inside-information disclosure evidence, insider-list workflows, alert explainability, model and rule provenance, reviewer decision trails, false-positive handling, investigation records, observability, change control, documentation, and compliance evidence handoff.
The purpose of this Skill is to increase awareness of potential gaps in the system and create engineering evidence for qualified review. The response produced by this Skill does not represent legal advice, a legal opinion, a determination of insider dealing, market manipulation, unlawful disclosure, reportability, jurisdiction, or a final regulatory determination.
The main question is:
When does a Java enterprise financial system require MAR-aware market-surveillance controls, and what should developers build differently?
External reference: Market Abuse Regulation (EU) No 596/2014.
Market Abuse Regulation chapters summary reference: MAR chapters summary.
Java engineering examples reference: MAR engineering examples.
Questionnaire asset: MAR engineering review questionnaire.
Report template asset: MAR engineering review report template.
This Skill applies to:
Treat insider dealing, unlawful disclosure, market manipulation, reportability of suspicious orders or transactions, disclosure-delay legality, financial-instrument scope, market-sounding interpretation, accepted market practices, sanctions, jurisdiction, and regulatory interpretation as governance decisions for legal, compliance, market-surveillance, risk, product, operations, and accountable business owners.
Engineering teams should still create evidence that makes those decisions reviewable:
test cases passed, vs 9 / 21 without
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