nwave-ai/nw-par-review-criteria

DevOp Reviewer: Review Criteria

Critique Dimension 1: Incomplete Phase Handoffs

Pattern: Phase handoffs missing required artifacts or approvals.

Required per Phase:

• DISCUSS: Requirements document + peer review approval
• DESIGN: Architecture document + ADRs + peer review approval
• DISTILL: Acceptance tests + peer review approval
• DELIVER: Production code + tests (100% passing) + peer review approval

Severity: critical. Verify all artifacts present and peer-reviewed before phase transition.

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Critique Dimension 2: Deployment Readiness Gaps

Pattern: Feature marked "ready" but missing production prerequisites.

Required: All tests passing (100%) | Production configuration complete | Monitoring/alerting configured | Runbook/operational docs created | Rollback plan documented.

Severity: critical. Complete missing prerequisite before marking deployment-ready.

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Critique Dimension 3: Traceability Violations

Pattern: Cannot trace production code back to requirements.

Required: User stories map to acceptance tests | Acceptance tests map to production code | Code changes traceable to commits | All AC verified in production.

Severity: high. Establish traceability chain: user-story -> acceptance-tests -> code-commits.

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Critique Dimension 4: Priority Validation

Purpose: Validate roadmap addresses largest bottleneck first, not secondary concern.

Questions

Q1: Is this the largest bottleneck? Does timing data show primary problem? Larger problem being ignored? Assessment: YES / NO / UNCLEAR.

Q2: Were simpler alternatives considered? Roadmap includes rejected alternatives? Rejection reasons evidence-based? Simpler solution achieves 80% benefit? Assessment: ADEQUATE / INADEQUATE / MISSING.

Q3: Is constraint prioritization correct? Constraints quantified by impact? Architecture addresses constraint-free opportunities first? Minority constraint dominating? (flag if >50% of solution for <30% of problem). Assessment: CORRECT / INVERTED / NOT_ANALYZED.

Q4: Is architecture data-justified? Key architectural decision supported by quantitative data? Different data leads to different architecture? Assessment: JUSTIFIED / UNJUSTIFIED / NO_DATA.

Failure Conditions

• FAIL if Q1 = NO (wrong problem being addressed)
• FAIL if Q2 = MISSING (no alternatives considered)
• FAIL if Q3 = INVERTED (minority constraint dominating)
• FAIL if Q4 = NO_DATA and this is performance optimization

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Critique Dimension 5: Functional Integration

Purpose: Verify feature wired into system entry point -- prevents Testing Theatre. A feature with 100% test coverage but 0% wiring tests is not complete.

Validation Criteria:

1. Wiring test exists: at least one acceptance test invokes feature through driving port
2. Component integrated: implemented component called from entry point module
3. Boundary correct: acceptance tests do not import internal components directly

Gate failure response: Block finalization | report specific integration gap with evidence | require integration step before completion.

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Quality Gate Checklist

Technical Completion

• [ ] All acceptance tests passing with stakeholder validation
• [ ] Unit test coverage meeting project standards (>=80%)
• [ ] Integration test validation of cross-component functionality
• [ ] Code review completed with approval
• [ ] Static analysis and security scan passed
• [ ] Performance tested under realistic load

Architecture Compliance

• [ ] Implementation aligns with architectural design
• [ ] Component boundaries and interfaces respected
• [ ] Security architecture implemented correctly

Production Readiness

• [ ] Monitoring and alerting configured
• [ ] Logging and debugging capability validated
• [ ] Rollback procedure documented and tested
• [ ] Operational runbook complete
• [ ] Support team trained / knowledge transferred

Business Completion

• [ ] All user stories completed with acceptance criteria met
• [ ] Business rules implemented and validated
• [ ] Stakeholder acceptance obtained