artifact-upcycle

To consolidate scattered artifacts, you can run a policy-driven Python script that normalizes filenames, adds metadata headers, and repairs cross-file links. This deterministic upcycling workflow transforms messy repositories into clean, structured outputs.

Artifact upcycling is the process of salvaging orphaned or stale files into structured outputs for reuse and archival. You need it when a repository contains mixed file types requiring deterministic transformations and metadata normalization to reduce fragmentation.

To safely archive stale content, the workflow enforces a dry-run by default and mandates archiving before any deletion. This one-action-per-pass invariant ensures stale content is safely moved to an archive directory without data loss.

Yes, you can use a Python-based policy-driven workflow to automate cross-file link repairs and metadata normalization. The script applies deterministic transformations across directories to ensure files are correctly wired and structured.

The one-action-per-pass limitation restricts the workflow to a single transformation per execution to enforce safety. This means complex multi-step file processing requires multiple sequential runs to complete the full upcycling and archival process.