multi-reviewer-patterns
π―SkillA guide for running a code review with several reviewers at once, each checking a different area such as security or speed. It shows how to merge duplicate findings, rate how serious each problem is, and write one combined report.
Installation
npx skills add wshobson/agents --skill multi-reviewer-patternsRun it in a terminal; it asks which AI coding tools to install it for (Claude Code, Codex, Cursor and more).
Uses skills.sh Β· Node.js 22.20+
After installing
Ask for related work and the agent uses it on its own, or call it yourself.
/multi-reviewer-patternsInstall by hand
Copy the whole skill folder from GitHub to the place below. Copying only SKILL.md can leave out files the skill uses.
Open the skill folder β- This project
.claude/skills/multi-reviewer-patterns/ - All projects
~/.claude/skills/multi-reviewer-patterns/
These paths are for Claude Code. For other tools, the command above puts it in the right place.
What this skill does
Overview
This skill helps you organize a code review done by several reviewers in parallel. Each reviewer looks at one area, such as security, speed, code structure, tests, or accessibility (how usable the app is for people with disabilities). The skill then shows how to turn all their notes into one clear report.
Key Features
- Pick which review areas to use based on what changed, such as an API or a screen in the app.
- Merge findings when two reviewers point to the same problem in the same line of code.
- Rate each problem as Critical, High, Medium, or Low using clear rules.
- Fill in a ready-made report template with a summary table by area and severity.
Who is this for?
This is for developers and teams who use AI agents or several people to review code. It helps when reviews come back messy, repeated, or rated differently. You get one report that is easy to act on.
Summarized by AI from this skill's SKILL.md. Suggest a better one
SKILL.md
View on GitHub βCoordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
Multi-Reviewer Patterns
Patterns for coordinating parallel code reviews across multiple quality dimensions, deduplicating findings, calibrating severity, and producing consolidated reports.
When to Use This Skill
- Organizing a multi-dimensional code review
- Deciding which review dimensions to assign
- Deduplicating findings from multiple reviewers
- Calibrating severity ratings consistently
- Producing a consolidated review report
Review Dimension Allocation
Available Dimensions
| Dimension | Focus | When to Include |
|---|---|---|
| Security | Vulnerabilities, auth, input validation | Always for code handling user input or auth |
| Performance | Query efficiency, memory, caching | When changing data access or hot paths |
| Architecture | SOLID, coupling, patterns | For structural changes or new modules |
| Testing | Coverage, quality, edge cases | When adding new functionality |
| Accessibility | WCAG, ARIA, keyboard nav | For UI/frontend changes |
Recommended Combinations
| Scenario | Dimensions |
|---|---|
| API endpoint changes | Security, Performance, Architecture |
| Frontend component | Architecture, Testing, Accessibility |
| Database migration | Performance, Architecture |
| Authentication changes | Security, Testing |
| Full feature review | Security, Performance, Architecture, Testing |
Finding Deduplication
When multiple reviewers report issues at the same location:
Merge Rules
- Same file:line, same issue β Merge into one finding, credit all reviewers
- Same file:line, different issues β Keep as separate findings
- Same issue, different locations β Keep separate but cross-reference
- Conflicting severity β Use the higher severity rating
- Conflicting recommendations β Include both with reviewer attribution
Deduplication Process
For each finding in all reviewer reports:
1. Check if another finding references the same file:line
2. If yes, check if they describe the same issue
3. If same issue: merge, keeping the more detailed description
4. If different issue: keep both, tag as "co-located"
5. Use highest severity among merged findings
Severity Calibration
Severity Criteria
| Severity | Impact | Likelihood | Examples |
|---|---|---|---|
| Critical | Data loss, security breach, complete failure | Certain or very likely | SQL injection, auth bypass, data corruption |
| High | Significant functionality impact, degradation | Likely | Memory leak, missing validation, broken flow |
| Medium | Partial impact, workaround exists | Possible | N+1 query, missing edge case, unclear error |
| Low | Minimal impact, cosmetic | Unlikely | Style issue, minor optimization, naming |
Calibration Rules
- Security vulnerabilities exploitable by external users: always Critical or High
- Performance issues in hot paths: at least Medium
- Missing tests for critical paths: at least Medium
- Accessibility violations for core functionality: at least Medium
- Code style issues with no functional impact: Low
Consolidated Report Template
## Code Review Report
**Target**: {files/PR/directory}
**Reviewers**: {dimension-1}, {dimension-2}, {dimension-3}
**Date**: {date}
**Files Reviewed**: {count}
### Critical Findings ({count})
#### [CR-001] {Title}
**Location**: `{file}:{line}`
**Dimension**: {Security/Performance/etc.}
**Description**: {what was found}
**Impact**: {what could happen}
**Fix**: {recommended remediation}
### High Findings ({count})
...
### Medium Findings ({count})
...
### Low Findings ({count})
...
### Summary
| Dimension | Critical | High | Medium | Low | Total |
| ------------ | -------- | ----- | ------ | ----- | ------ |
| Security | 1 | 2 | 3 | 0 | 6 |
| Performance | 0 | 1 | 4 | 2 | 7 |
| Architecture | 0 | 0 | 2 | 3 | 5 |
| **Total** | **1** | **3** | **9** | **5** | **18** |
### Recommendation
{Overall assessment and prioritized action items}
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