Agentic coding creates a new review problem.
The reviewer is not only reading a diff. They are judging whether an agent understood a ticket, used the right context, changed the right files, ran the right checks, and stopped at the right boundary.
A review packet solves that problem by giving reviewers a concise evidence summary with links to detail.
What a Review Packet Is
A review packet is the structured summary attached to an AI-generated PR/MR.
It should answer:
- What approved work started this run?
- What did the agent attempt?
- What files changed?
- What validation ran?
- What failed and was repaired?
- What risks or gaps remain?
- What should the human reviewer focus on?
The packet does not replace review. It makes review more focused.
MergeLoom’s Quality Agents are built around this pre-review path: validate, repair where appropriate, inspect scope, and prepare handoff evidence.
Template: PR/MR Review Packet
Use this structure as a starting point.
## Source Work
- Ticket: ABC-123- Requester:- Owning team:- Target repository:- Work type:- Risk level:
## Implementation Summary
- What changed:- Why this approach:- Main files touched:- Out of scope:
## Acceptance Criteria Mapping
- [ ] Criterion 1:- [ ] Criterion 2:- [ ] Criterion 3:
## Validation Evidence
- Setup:- Format:- Lint:- Typecheck:- Tests:- Build:- Custom checks:
## Repair History
- Attempt 1:- Attempt 2:- Stopped conditions:
## Diff Scope
- Files changed:- Lines changed:- Restricted paths touched:- Generated files changed:- Lockfiles changed:
## Known Gaps
- Checks skipped:- Environment limitations:- Manual verification needed:
## Reviewer Focus Areas
- Behaviour:- Security:- Data handling:- Tests:- Architecture:
## Audit Links
- Run record:- Logs:- Validation output:- Related PRs/MRs:Keep the packet short enough that reviewers will read it. Link to logs and run records for detail.
Section 1: Source Work
The packet should start with the approved work item.
Include:
- ticket link
- requester
- owning team
- target repository
- work type
- risk level or risk notes
This keeps the PR/MR tied to normal planning and approval systems. It also helps reviewers reject work that does not match the approved ticket.
For intake guidance, read Ticket Template for AI Coding Agents.
Section 2: Implementation Summary
The implementation summary should be plain and concrete.
Good:
- Added server-side validation for missing account IDs before creating invoices.
- Updated the existing invoice service path instead of adding a new helper because related validation already lives there.
- Changed tests in the existing service test file.
Poor:
- Improved invoice handling.
- Made the system better.
- Refactored billing.
Reviewers need intent, not marketing language.
Section 3: Acceptance Criteria Mapping
Map each acceptance criterion to the implementation.
This makes it easier to spot missing work and scope drift. If the ticket has no acceptance criteria, the run should probably stop before PR/MR handoff or clearly state the gap.
Acceptance criteria mapping is also useful when teams measure AI coding adoption. It separates “the agent changed code” from “the agent addressed the requested work.”
Section 4: Validation Evidence
Validation evidence is the heart of the packet.
Include:
- commands run
- pass/fail result
- short output summary
- links to full logs
- checks skipped and why
Do not hide skipped checks. A skipped test may be acceptable if the environment is unavailable, but the reviewer should know.
For a deeper validation model, read AI code validation before PR.
Section 5: Repair History
If the agent repaired failures, the reviewer should see the repair story.
Capture:
- what failed
- what changed during repair
- whether validation passed afterwards
- how many repair attempts ran
- whether repair stopped due to a limit
Repair history prevents a clean final diff from hiding a messy run.
Section 6: Diff Scope
Diff scope tells reviewers whether the change stayed inside the approved boundary.
Include:
- files changed
- unexpected directories
- restricted paths
- generated files
- lockfiles
- public API or schema changes
MergeLoom’s Diff Guard, part of Quality Agents, is designed for this type of scope check.
Section 7: Reviewer Focus Areas
The packet should tell reviewers where human judgment matters most.
Examples:
- Confirm the API behaviour matches product expectations.
- Check whether the fallback state is acceptable for empty accounts.
- Review the migration path before merge.
- Confirm the test fixture represents real data.
Do not ask reviewers to re-run every basic check if the platform already captured that evidence. Use their time for judgment.
Where MergeLoom Fits
MergeLoom prepares AI-generated work for human review by connecting the source ticket, context, validation, repair history, Diff Guard, audit evidence, and PR/MR handoff.
To apply this review model, explore Ticket-To-Code Automation or book a demo to map the review packet your teams need.