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review-team

Coordinate evidence-based code reviews across rigs and pods in OpenRig.

60|9|Updated Apr 1, 2026
Search Tags:#review#code-review#anti-slop#context-priming#empirical-verification#rig-management
One-click install
npx skills add https://github.com/mvschwarz/openrig --skill review-team-mvschwarz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-team
Source: https://github.com/mvschwarz/openrig/tree/main/packages/daemon/specs/agents/shared/skills/pods/review-team
Command: npx skills add https://github.com/mvschwarz/openrig --skill review-team-mvschwarz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Complete operating manual for the review pod, outlining standardized procedures for context priming, anti-slop discipline, empirical verification, and the deep review workflow (independent → cross-exam → convergence → roundtable).

Core Features & Use Cases

  • Context priming before any review to ensure codebase understanding
  • Anti-slop analysis to avoid divergent implementation paths
  • Empirical verification with structured evidence gathering
  • Phase-driven workflow covering independent review, cross-examination, convergence, and documentation
  • Artifact management and reviewer behavioral awareness to improve quality and consistency

Quick Start

Follow the review-team protocol to prepare a context proof and initiate a full roundtable review sequence.

Frequently Asked Questions about review-team

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

FAQPage Schema
How do I run structured code reviews at scale across multiple development teams?▼

Structured code reviews at scale require a standardized protocol enforcing context priming, anti-slop analysis, and empirical verification. This coordinates independent reviews, cross-examinations, and convergence roundtables to ensure evidence-based design and implementation validation.

What is anti-slop analysis in a code review workflow?▼

Anti-slop analysis is a code review discipline preventing divergent implementation paths by enforcing rigorous context priming. It ensures reviewers deeply understand the codebase before evaluating changes, avoiding superficial or misaligned feedback during cross-examination.

How do I implement empirical verification during a deep code review?▼

Empirical verification during deep code reviews requires structured evidence gathering to validate design and implementation choices. Reviewers independently analyze artifacts, cross-examine findings, and converge during a roundtable to finalize phase-driven reporting.

Can I coordinate independent code reviews and convergence roundtables within an automated rig management system?▼

Yes, automated rig management systems can coordinate independent code reviews and convergence roundtables by applying a standardized deep-review protocol. This guides pods through context priming, cross-examination, and artifact management to produce phase-driven reports.

What is the best way to prevent divergent implementation paths during cross-examination reviews?▼

Preventing divergent implementation paths during cross-examination requires anti-slop analysis and context priming before review. Reviewers prepare a context proof to establish codebase understanding, ensuring the convergence roundtable stays empirically grounded.

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