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codex-review

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UpdatedApril 12, 2026 at 17:05

Professional code review with auto CHANGELOG generation, integrated with Codex AI. Use when you want professional code review before commits, you need automatic CHANGELOG generation, or reviewing large-scale refactoring.

Installation

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

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techwavedev

techwavedev/agi-agent-kit

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Related occupationsSOC

Based on SOC occupation classification

Software DevelopersComputer and Mathematical Occupations·SOC 15-1252

SKILL.md

readonly

name	codex-review
description	Professional code review with auto CHANGELOG generation, integrated with Codex AI. Use when you want professional code review before commits, you need automatic CHANGELOG generation, or reviewing large-scale refactoring.
risk	unknown
source	community
date_added	2026-02-27

codex-review

Overview

Professional code review with auto CHANGELOG generation, integrated with Codex AI

When to Use

When you want professional code review before commits
When you need automatic CHANGELOG generation
When reviewing large-scale refactoring

Installation

npx skills add -g BenedictKing/codex-review

Step-by-Step Guide

Install the skill using the command above
Ensure Codex CLI is installed
Use /codex-review or natural language triggers

Examples

See GitHub Repository for examples.

Best Practices

Keep CHANGELOG.md in your project root
Use conventional commit messages

Troubleshooting

See the GitHub repository for troubleshooting guides.

Related Skills

context7-auto-research, tavily-web, exa-search, firecrawl-scraper

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency.

# Check for prior AI agent orchestration context before starting
python3 execution/memory_manager.py auto --query "agent patterns and orchestration strategies for Codex Review"

Storing Results

After completing work, store AI agent orchestration decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \
  --type decision --project <project> \
  --tags codex-review ai-agents

Multi-Agent Collaboration

This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \
  --project <project>

Control Tower Integration

Register agents and tasks with the Control Tower (execution/control_tower.py) for centralized orchestration across machines and LLM providers.

Blockchain Identity

Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems.

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name	codex-review
description	Professional code review with auto CHANGELOG generation, integrated with Codex AI. Use when you want professional code review before commits, you need automatic CHANGELOG generation, or reviewing large-scale refactoring.
risk	unknown
source	community
date_added	2026-02-27

codex-review

Overview

Professional code review with auto CHANGELOG generation, integrated with Codex AI

When to Use

When you want professional code review before commits
When you need automatic CHANGELOG generation
When reviewing large-scale refactoring

Installation

npx skills add -g BenedictKing/codex-review

Step-by-Step Guide

Install the skill using the command above
Ensure Codex CLI is installed
Use /codex-review or natural language triggers

Examples

See GitHub Repository for examples.

Best Practices

Keep CHANGELOG.md in your project root
Use conventional commit messages

Troubleshooting

See the GitHub repository for troubleshooting guides.

Related Skills

context7-auto-research, tavily-web, exa-search, firecrawl-scraper

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency.

# Check for prior AI agent orchestration context before starting
python3 execution/memory_manager.py auto --query "agent patterns and orchestration strategies for Codex Review"

Storing Results

After completing work, store AI agent orchestration decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \
  --type decision --project <project> \
  --tags codex-review ai-agents

Multi-Agent Collaboration

This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \
  --project <project>

Control Tower Integration

Register agents and tasks with the Control Tower (execution/control_tower.py) for centralized orchestration across machines and LLM providers.

Blockchain Identity

Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems.