mandu-po-assistant

Refining product backlog items involves systematically analyzing descriptions, comments, and attachments to detect ambiguities, then generating a normalized functional specification ready for technical review. This ensures teams share a clear business understanding before development begins.

Generating functional specifications from ambiguous backlog items involves leveraging a REST API for Azure DevOps to iteratively question the Product Owner, resolving contradictions and producing a structured, normalized description with full traceability for technical teams.

Yes, managing requirements through this backlog refinement process requires Python 3.10 or higher. Additionally, you need specific dependencies like python-docx, requests, and PyYAML installed to process attachments and execute the clarification scripts.

The best way to normalize incomplete PBIs is through guided, grouped clarification questions directed at the Product Owner, which resolves critical doubts and produces a structured functional specification that guarantees common understanding.

Automated backlog refinement for requirement specification is not suitable when you lack access to Azure DevOps REST APIs, or when your PBIs lack textual descriptions and attachments, as the systematic analysis depends on extracting and processing these existing inputs.