A newer class of tools uses LLM-based agents to check arc42 documentation section by section against what arc42 expects. This complements, rather than replaces, a human review.

One example is arc42agentic, an open-source agent system you can use with agentic coding assistants (e.g. VS Code with GitHub Copilot, or via APM). It reviews each section against the arc42 requirements, and additionally runs cross-section consistency checks: do your quality goals (section 1) match your solution strategy (section 4)? Does your context (section 3) match your building blocks (section 5)?

This isn’t specific to section 1: the same approach applies across all twelve sections.

Note: treat the output as a structured first review, not a replacement for your own judgement. Apply the same scrutiny you’d give any LLM output.