skills.rest
D3Hunter
D3HunterCOMMUNITY
Explore all skills by this author →
GitHub

review-output-format

Format code review findings into severity-sorted JSON with rubric metadata.

Updated Mar 3, 2026
Search Tags:#code review#json schema#engineering workflow#output formatting#review findings#severity ranking#rubric fields
One-click install
npx skills add https://github.com/D3Hunter/ai-engineer --skill review-output-format
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-output-format
Source: https://github.com/D3Hunter/ai-engineer/tree/main/skills/review-output-format
Command: npx skills add https://github.com/D3Hunter/ai-engineer --skill review-output-format

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Unstructured, inconsistent code review output makes it difficult for engineering teams to prioritize critical issues, track actionable fixes, and integrate review feedback into downstream project management and development workflows. This Skill eliminates that friction by enforcing a strict, uniform format for all review findings.

Core Features & Use Cases

  • Strict JSON Schema Enforcement: Ensures all review output is a valid JSON object with a required top-level findings array, eliminating malformed output that breaks downstream tooling.
  • Severity-Based Sorting: Mandates that findings are ordered by risk (highest first) so critical blockers and major issues are addressed immediately, rather than getting lost in unstructured feedback.
  • Standardized Rubric Fields: Requires non-trivial findings to include clear context (why, scope), risk assessment (risk_if_unchanged), concrete evidence, and actionable change_request details, so every review comment is clear and actionable.
  • Use Case: For engineering teams running pull request reviews or code audits, this Skill ensures all feedback is uniform, easy to triage, and compatible with issue tracking and reporting tools.

Quick Start

Use the review-output-format skill to format all identified code review findings into a valid, severity-sorted JSON object with complete rubric details for each actionable issue.

Frequently Asked Questions about review-output-format

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I format code review findings into a structured JSON schema?▼

Format code review findings into a structured JSON schema by enforcing a required top-level findings array with standardized rubric fields, ensuring output is valid for downstream engineering tooling integration.

How do I sort code review findings by severity for pull request reviews?▼

Sort code review findings by severity by mandating that all identified issues are ordered by risk level, placing critical blockers and major issues first so engineering teams can prioritize immediate fixes during pull request reviews.

What is a standardized rubric for code review output and when do I need it?▼

A standardized rubric for code review output is a set of mandatory metadata fields including context, risk assessment, evidence, and change requests. It is needed for non-trivial findings to ensure every review comment is clear, actionable, and easy to triage.

Can I integrate structured JSON review findings with issue tracking tools?▼

Yes, you can integrate structured JSON review findings with issue tracking tools because the strict top-level JSON schema enforcement eliminates malformed output, making the formatted feedback compatible with downstream project management and reporting workflows.

What are the limitations of using a strict JSON schema for code review formatting?▼

The limitation of using a strict JSON schema for code review formatting is that all findings must adhere to mandatory severity fields and complete rubric details, which may require additional processing overhead for trivial issues that do not fit the structured format.

What is the best way to standardize code audit results for engineering workflows?▼

The best way to standardize code audit results for engineering workflows is to apply a fixed top-level JSON schema that requires severity-based sorting and actionable change requests, producing uniform feedback compatible with static analysis reporting.

Related Skills

Explore More Software Engineering Skills→
jewzaamjewzaam

apply-review

Apply findings from Findings-*.json as isolated commits after schema validation.

Community
Advanced
atomicinnovationatomicinnovation
30

pr-review-output-format

Define a standardized JSON output format for pull request review agents.

Official
Basic
FC-FUZFC-FUZ
12

security

Automate security analysis of code changes with Trail of Bits tools.

Community
Advanced
wiltaylorwiltaylor

review-pr

Generate structured JSON feedback from pull request diffs.

Community
Intermediate