by longranger2 · Claude Skill · ★ 66
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Claude-GPT Workflow Skills 中文 | English A collection of Claude Code skills for Claude + GPT automatic collaboration workflows. Skills codex Delegates coding tasks to Codex CLI for execution. CodeX is a cost-effective, strong coder — great for batch refactoring, code generation, multi-file changes, and multi-turn implementation tasks. Based on oil-oil/codex. Usage: plan-review Reviews a technical plan via Codex and iteratively refines it. Uses adversarial review to improve plan quality before implementation. Trigger: plan-execute Executes a finalized plan by delegating coding to Codex. Claude orchestrates, Codex codes, Claude reviews, Codex fixes — iterating until quality passes. Trigger: Note After Claude enters mode, plan files are stored under by default. You can change the plan storage directory in ; for example, the config below stores plans in the current project's directory: Installation Option 1: npx skills add (Recommended) Option 2: Manual installation Copy skills to your Clau
| Stars | 66 |
| Forks | 8 |
| Language | Shell |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 70.2751739701413/100 |
| Last Updated | 2026-06-24 |
| Created | 2026-03-09 |
| Platforms | claude-code, cli, codex |
| Est. Tokens | ~3k |
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claude-gpt-workflow is Claude Code skills for Claude + GPT collaborative workflows. Adversarial plan review + orchestrated code execution with iterative refinement.. It is categorized as a Claude Skill with 66 GitHub stars.
claude-gpt-workflow is primarily written in Shell. It covers topics such as ai-wor, claude, claude-code.
You can find installation instructions and usage details in the claude-gpt-workflow GitHub repository at github.com/longranger2/claude-gpt-workflow. The project has 66 stars and 8 forks, indicating an active community.
claude-gpt-workflow is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-gpt-workflow on Agent Skills Hub include agnix, claude-emporium, deepcontext-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.