Describe the generated change
Record the affected area, model or assistant, prompting context and the human responsible for acceptance.
Free AI change-record tool
AI Code Provenance Log Builder
Create a provenance record for AI-assisted code changes, prompts, models, reviewers and verification evidence, with a calculated audit score.
- Calculated instantly from your inputs
- No signup or data submission
- A focused next step for MVP planning
Your entries remain in this browser session and are not sent to MVPHub.
Your inputs
Keep generated changes attributable and reviewable
The score checks whether the record identifies the change, model, prompt lineage, affected files, reviewer and verification evidence.
Your calculated result
Your result
0/100
Planning score
Recommended next actions
How it works
Measure traceability
The score checks whether source context, material edits, tests, licensing considerations and reviewer evidence are recorded.
Generate the log entry
The result produces a concise provenance record suitable for a pull request, decision log or internal audit trail.
Frequently asked questions
Does provenance prove that generated code is safe?
No. It documents origin and review evidence; security, correctness and licensing still require their own checks.
Should the complete prompt be stored?
Only when policy permits it. A redacted summary and references to approved internal records may be safer than storing sensitive context.
What changes deserve a provenance entry?
Prioritize material generated code, architecture changes, dependencies and security-sensitive logic rather than trivial completions.
How we compare
| Capability | MVPHub | GitHub | GitLab |
|---|---|---|---|
| Change-linked record fields | ✓ | ✓ | ✓ |
| AI review evidence prompts | ✓ | — | — |
| Traceability completeness score | ✓ | — | — |
MVPHub drafts a focused AI-code provenance entry. GitHub and GitLab retain commits, reviews and project history where an approved provenance record can be stored.