Codex Workflows
Development workflows for Codex that keep technical rigor and edge-case handling from becoming product overengineering.
Install
npx codex-workflows installclaude mcp add codex-workflows -- npx codex-workflows install{
"mcpServers": {
"codex-workflows": {
"command": "npx",
"args": [
"codex-workflows",
"install"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →codex-workflows
English | 简体中文 | 日本語 | Español | 한국어 | Português (Brasil)
On larger product work, Codex can pursue technical consistency beyond what the user needs. Handling every edge case and making each path deterministic can alter what users see even when the approved outcome does not require it.
codex-workflows keeps that work within the smallest approved outcome. It confirms which user-visible behavior may change, records what must not, and requires evidence before completion. Within those boundaries, Codex chooses reversible implementation details from the repository.
The workflows are installed as Agent Skills and custom agents for OpenAI Codex CLI. The main Codex session checks scope and rough cost before design, owns progress and review decisions, and carries approved work through implementation and independent verification.
Why not use Codex directly?
Direct Codex is the better fit for a well-scoped fix, disposable experiment, or one-shot script. It is faster and cheaper when the intended outcome and safe implementation boundary are already clear.
Use codex-workflows when technical choices can change the product scope, user-visible behavior, or a decision that needs to survive across contexts.
For example, a request to extend an existing authentication path can lead to a technically cleaner second mechanism, broader validation, and a new response contract. The frontend may adapt and the tests may pass, while users receive behavior that was never part of the approved change.
codex-workflows controls that expansion throughout the run:
| Control | What changes |
|---|---|
| Scope | The workflow compares the request with the desired outcome, explicit exclusions, the existing code, and rough implementation cost. Work that does not earn its cost is removed before it becomes architecture, and cut back later if it got in anyway. |
| Phase gates | Requirements, design, and planning outputs are checked before they can authorize the next phase. Fresh agents read the approved decisions and evidence they need instead of reconstructing intent from a long conversation. |
| Execution | Once you authorize implementation, Codex executes the task set autonomously. Each task passes its focused verification and applicable repository checks before its implementation commit. |
| Completion | Independent code and security reviews check that the completed change stays within the approved scope and has no serious problems. Required corrections return through the same implementation and quality cycle. |
This workflow uses more agent calls and tokens than direct execution. Use it when protecting the approved outcome is worth that cost. When a change does not need every check, lite mode runs fewer of them.
An edge case does not require work simply because Codex can handle it. Additional validation, deterministic behavior, or a new abstraction must protect an approved requirement, an observable contract, or a demonstrated failure. This cuts both ways: when a design decision turns out to carry more than the outcome needs, the workflow removes it instead of defending it because a document already named it.
A real workflow run
Similar plugs
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local…
Why use many token when few token do trick. Viral skill + proxy for coding agents that cuts 65% of tokens by talking like a caveman.
Production-grade engineering skills for AI coding agents.
The 1st Collaborative AI Design Agent Workspace. Local-first and open source. Create prototypes, websites, apps, dashboards, presentations, images, and videos with your team…