When ME and not audit-industrialisation

• ME when: an audit targeting this domain only
• audit-industrialisation instead if: a global multi-domain audit - it orchestrates every audit (including ME) and produces a consolidated report

For a full project audit, use audit-industrialisation rather than invoking each skill separately.

QA & DevOps + Data Quality Audit

Overview

Audit a project's maturity across two sections (28 questions), scored 0-4 per question:

• QA & DevOps (16 questions): test coverage, CI/CD, code quality, dependency security, observability, code review, DORA metrics - grid in reference/qa-devops.md
• QU - Data quality (12 questions): schema validation, null handling, business consistency, anomaly correction, traceability, data lifetime - grid in reference/qu-qualite-donnees.md

Score calculation

• Domain score = average of ALL scored questions across both sections (flat mean, exclude N/A - per audit-report/reference/scoring-model.md; do NOT average the two section means)
• Section means may be shown for readability, but they do not enter the domain score
• State "X questions scored out of Y total" per section
• A question is N/A if the project profile makes it non-applicable

Audit protocol

1. Identify the project type: backend, frontend SPA, fullstack, library, microservices. Mark questions N/A according to the context.
2. QA & DevOps section: read reference/qa-devops.md. For each question QA-01 to QA-14, run the listed bash commands, assign a level 0-4 (or N/A) with a justification and a confidence.
3. QU - Data quality section: read reference/qu-qualite-donnees.md. For each question QU-01 to QU-09a, run the listed bash commands, assign a level 0-4 (or N/A) with a justification and a confidence.
4. Calculate the scores according to the rules above.
5. Produce the report in the output format below.

Grids by section

Each grid contains, per question: statement, criticality (must/should/could), items to analyze and check, bash commands, and the table of levels 0-4.

Output format

## QA & DevOps + Data Quality - Global score: X.X/4

### Summary
[2-3 sentences summarizing quality maturity across the two sections]

### QA & DevOps section - Score: X.X/4 (Y questions scored out of 16)

| Code | Question | Criticality | Level | Confidence | Justification |
|------|----------|-------------|-------|------------|---------------|
| QA-01 | Test coverage | must | X | high/medium/low | ... |
| QA-01a | Test strategy by criticality | should | X | high/medium/low | ... |
| QA-02 | Post-deployment smoke tests | must | X | high/medium/low | ... |
| QA-03 | Single artifact promotion | should | X | high/medium/low | ... |
| QA-04 | CI/CD quality gates | must | X | high/medium/low | ... |
| QA-05 | CI/CD feedback speed | should | X | high/medium/low | ... |
| QA-06 | Code quality & debt | should | X | high/medium/low | ... |
| QA-07 | Dependency security (SCA) | must | X | high/medium/low | ... |
| QA-07a | Dependency updates | should | X | high/medium/low | ... |
| QA-08 | Incident reproducibility | should | X | high/medium/low | ... |
| QA-09 | Realistic datasets | should | X | high/medium/low | ... |
| QA-10 | Application profiling | could | X | high/medium/low | ... |
| QA-11 | CI/CD security | must | X | high/medium/low | ... |
| QA-12 | Product observability | should | X | high/medium/low | ... |
| QA-13 | Code review | must | X | high/medium/low | ... |
| QA-14 | DORA metrics | should | X | high/medium/low | ... |

### QU Data Quality section - Score: X.X/4 (Y questions scored out of 12)

| Code | Question | Criticality | Level | Confidence | Justification |
|------|----------|-------------|-------|------------|---------------|
| QU-01 | Input schema validation | must | X | high/medium/low | ... |
| QU-01a | Validation errors | should | X | high/medium/low | ... |
| QU-02 | Null/incomplete handling | should | X | high/medium/low | ... |
| QU-03 | Business consistency | must | X | high/medium/low | ... |
| QU-03a | Data anomaly detection | could | X | high/medium/low | ... |
| QU-04 | Manual anomaly correction | should | X | high/medium/low | ... |
| QU-05 | Automatic anomaly correction | could | X | high/medium/low | ... |
| QU-06 | Correlation ID (traceId) | should | X | high/medium/low | ... |
| QU-07 | Technical logs / business events separation | should | X | high/medium/low | ... |
| QU-08 | Data lifetime | must | X | high/medium/low | ... |
| QU-09 | Automatic purges | should | X | high/medium/low | ... |
| QU-09a | Purge verification | could | X | high/medium/low | ... |

### Strengths
- ...

### Weaknesses
- ...

### Recommendations
1. [MUST] ...
2. [SHOULD] ...
3. [COULD] ...

### Non-auditable items
- [List here any item impossible to verify by static analysis: runtime metrics, real performance, etc.]

Exit condition

• Project type identified, N/A questions marked
• The 16 QA questions scored 0-4 or N/A, with justification and confidence
• The 12 QU questions scored 0-4 or N/A, with justification and confidence
• Verification commands executed for every scored question
• Section scores and global score calculated (N/A excluded)
• Report produced in the output format