Scenario 5: Claude Code for Continuous Integration

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.

Passage quoted verbatim from the official CCAR-F exam guide v1.0, section 5.

This scenario on the exam

Scenario: 5 of 6 — four are dealt at random
Primary domains: 2
Questions in this hive: 36

Primary domains

Claude Code Configuration & Workflows
Prompt Engineering & Structured Output

What the exam asks inside this context

Running non-interactively. -p, or the job hangs. Then --output-format json with --json-schema, because inline PR comments need parseable findings rather than prose to scrape.
Precision over emphasis. Explicit categorical criteria — report bugs and security, skip minor style — rather than asking for high-confidence findings only.
Independent review. The session that generated the code is the worst reviewer of it, because it holds the reasoning that produced the mistake.
Repeat runs. Prior findings go into context with an instruction to report only new or unaddressed issues, or every re-run posts the same comments again.

Scenario 5: Claude Code for Continuous Integration

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.

Passage quoted verbatim from the official CCAR-F exam guide v1.0, section 5.

This scenario on the exam

Scenario: 5 of 6 — four are dealt at random
Primary domains: 2
Questions in this hive: 36

What the exam asks inside this context

Running non-interactively. -p, or the job hangs. Then --output-format json with --json-schema, because inline PR comments need parseable findings rather than prose to scrape.

Precision over emphasis. Explicit categorical criteria — report bugs and security, skip minor style — rather than asking for high-confidence findings only.

Independent review. The session that generated the code is the worst reviewer of it, because it holds the reasoning that produced the mistake.

Repeat runs. Prior findings go into context with an instruction to report only new or unaddressed issues, or every re-run posts the same comments again.