knowledge-capture

Capture code-derived decisions by generating structured candidate knowledge records with code provenance during repository analysis, forwarding them through a governed transport for human approval. This prevents valuable engineering decisions discovered during code review from being lost.

Recording micro-decisions during reverse engineering involves creating capture manifests for code-derived patterns and forwarding them through a validated kcapture transport. Candidates are tracked with provenance separation and require human approval before submission via kmint.

Yes, kcapture transport integration is required to register code-derived knowledge candidates. The workflow mandates manifest validation, provenance separation, and human-gated submission through kmint to ensure controlled knowledge registration.

No, you cannot write discovered architectural rules directly into the knowledge base. The process requires creating refinement candidates with code provenance that undergo validation and human approval before entering the knowledge lifecycle.

Provenance tracking for candidate knowledge captures separates the code origin from the submitted knowledge entry. This separation ensures the architectural rule or implementation pattern is validated and human-gated before registration through kmint.

Use a governed knowledge registration workflow when you need to capture code review decisions as refinement candidates with provenance tracking. It applies to software engineering scenarios involving architecture discovery and knowledge registration requiring human approval.