consensus-review

Distribute inputs to multiple agents and aggregate structured consensus findings.

Updated Aug 23, 2026

Search Tags:#automation #planning #multi-agent #consensus #review #code-review #ui-review

Ready to run

npx skills add https://github.com/daniyarseifolla/agent-skills --skill consensus-review-daniyarseifolla

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: consensus-review
Source: https://github.com/daniyarseifolla/agent-skills/tree/main/v2.2/core/consensus-review
Command: npx skills add https://github.com/daniyarseifolla/agent-skills --skill consensus-review-daniyarseifolla

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinates multiple independent reviewers to uncover issues that single-agent reviews miss, improving accuracy and coverage in software assessments.

Core Features & Use Cases

Parallel, sectioned reviews: dispatches 2-3 agents per section to generate diverse findings.
Aggregation with conflict handling: combines results into a consensus report, flagging disagreements for user review.
Applicable patterns: code reviews, UI reviews, plan reviews, and attach-like state assessments.

Quick Start

Initiate a consensus review on the latest changes to obtain sectional consensus findings.

Frequently Asked Questions about consensus-review

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

FAQPage Schema

How does multi-agent consensus review improve code quality assessments?▼

Multi-agent consensus review improves code quality by dispatching a common input to multiple independent agents, combining their parallel findings into a structured report that flags disagreements and catches issues single-agent reviews miss.

What is the best way to run parallel UI reviews with conflict handling?▼

The best way to run parallel UI reviews with conflict handling is using a sectioned workflow that dispatches multiple agents per section, aggregates their findings sequentially, and flags disagreements for user review.

How do I aggregate multi-agent code review findings into a final report?▼

You aggregate multi-agent code review findings by implementing an intermediate file workflow that performs per-section aggregation on parallel prompts, producing a final consensus report with scoring and recommendations.

Can I use a consensus review workflow for plan assessments?▼

Yes, you can use a consensus review workflow for plan assessments by applying its sectioned workflows and parallel prompts to distribute the plan across independent agents for sequential aggregation.

Why do single-agent code reviews miss structural issues?▼

Single-agent code reviews miss structural issues because they lack the diverse findings generated by parallel, sectioned reviews where multiple independent agents evaluate the same input and surface disagreements through aggregation.

When should I not use multi-agent consensus reviews?▼

You should not use multi-agent consensus reviews when a rapid, linear assessment is sufficient, as the intermediate file workflow, parallel prompt dispatch, and sequential aggregation add processing overhead for comprehensive coverage.