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Use when reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of Plinth Toolkit
Passed 19 of 21 test cases with the skill, and 13 of 21 without it.
and 4 more in the full report
7 fixed13 passed either way1 still failing1 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 deploying a Spring Boot application that integrates OpenAI via LangChain4j for automated customer service routing and RAG retrieval. We need an ISO/IEC 42001 AI management system assessment of this Java service before our upcoming security and release review. Please evaluate our system context, data boundaries, and prompt flows, and generate a formal engineering review report that lists our scope, evidence gaps, identified risk signals, recommended controls, owner handoffs, and a recommended action plan.
| Checked | Without skill | With skill |
|---|---|---|
| States explicitly that legal advice, certification advice, audit conclusions, official interpretation, final risk acceptance, and final conformity decisions require qualified owner review. | Missed | Passed |
| Frames assessment findings as engineering controls and evidence gaps rather than declaring formal compliance verdicts. | Missed | Passed |
The instructions your model reads when the skill loads.
Use this Skill to review Java enterprise applications, delivery pipelines, AI-assisted development workflows, LLM integrations, RAG systems, AI agents, generated code, generated dependencies, external model-provider usage, prompt handling, and AI-enabled business logic through an ISO/IEC 42001 AI management system lens.
Apply this Skill to determine what engineering controls, evidence, lifecycle governance, risk treatment, monitoring, and owner handoffs are needed before GenAI-assisted Java work is merged, released, connected to enterprise systems, or relied on for business behavior.
This Skill is not legal advice, certification advice, audit advice, an audit conclusion, or a final conformity decision. It helps Java engineers, architects, tech leads, platform teams, security teams, AI governance reviewers, product teams, and reviewers identify when ISO/IEC 42001 AI management system concerns may apply and how to translate them into engineering controls such as AI inventory records, risk treatment, prompt and data governance, secure generated-code review, dependency provenance, model-provider boundaries, monitoring, corrective action, and qualified owner escalation.
The purpose of this Skill is to increase awareness of potential gaps in GenAI Java delivery and create reviewable engineering evidence for qualified owners. The response produced by this Skill does not represent legal advice, certification readiness, audit findings, compliance approval, or final conformity with ISO/IEC 42001.
The main question is:
What should a Java team build, review, document, and escalate so GenAI development and AI-enabled Java systems are governed as part of an AI management system?
Source provenance: ISO/IEC 42001 public overview material and issue #939 were reviewed while authoring the bundled references. Official source references include:
Do not fetch or ingest external regulatory, standard, certification, or audit web pages at runtime. Use the bundled references and escalate interpretation, certification, audit, legal, compliance, and conformity questions to qualified owners.
ISO/IEC 42001 summary reference: ISO/IEC 42001 AI management system summary.
Java engineering examples reference: ISO/IEC 42001 GenAI Java engineering examples.
Questionnaire asset: ISO/IEC 42001 engineering review questionnaire.
Report template asset: ISO/IEC 42001 engineering review report template.
This Skill applies to:
test cases passed, vs 13 / 21 without
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