pr-review-output-format

A standardized JSON output format for automated PR review agents provides a strict, machine-readable schema covering lens attribution, line-anchored comments, and severity tagging. This structure prevents ambiguous natural-language outputs, ensuring orchestrators can parse and post findings as GitHub comments.

To structure multi-agent code review findings for GitHub inline comments, output a strict JSON block containing lens attribution (e.g., security, correctness), a summary, strengths, and line-anchored comments. This allows an orchestrator to merge feedback from multiple agents into harmonized GitHub reviews.

Yes, your PR review agent needs a strict JSON schema for orchestrator parsing if you want to automate posting feedback. Enforcing JSON-only output ensures the orchestrator can reliably extract severity, confidence, and file path anchoring to generate inline GitHub comments without manual editing.

Required fields for line-anchored comments in automated code review workflows include lens attribution, file path anchoring, multi-line ranges, severity, and confidence tagging. These review-oriented fields ensure consistent reviewer communication and precise placement of automated feedback on GitHub.

You need to use a JSON schema for pull request review automation when combining multiple agent lenses, such as security and performance, into a single workflow. It specifies field-level requirements for general findings grouping and comment anchoring, enabling orchestrators to merge and post feedback seamlessly.

No, you should not use natural language summaries instead of JSON for multi-agent code review if automating the workflow. Natural language creates ambiguous outputs that orchestrators cannot parse, whereas a strict JSON schema with severity, confidence, and lens attribution enables deterministic merging and posting of GitHub comments.