Codex handles one-shot tasks well. Multi-file features? You end up planning, scoping, and verifying yourself. codex-workflows automates that. Your request becomes a design doc, atomic tasks, and TDD implementation — each in a dedicated subagent context. By the time you see the result, quality checks have already passed. Counterpart of claude-code-workflows, built for Subagents and GPT models.
codex-workflows
Codex is already good at one-shot changes. The gap shows up when a task touches multiple files — you start doing the planning, scoping, and verification yourself, which is exactly the work agents should handle.
codex-workflows fills that gap. It sets up specialized subagents that take a request through requirements, design, task decomposition, TDD implementation, and quality checks — each step in its own context, each task landing as one commit.
What happens when you run a recipe
$recipe-implement Add user authentication with JWT
The framework picks the right level of structure based on scope:
- 1-2 files: simplified plan, direct implementation
- 3-5 files: Design Doc, work plan, task execution
- 6+ files: PRD, ADR, Design Doc, test skeletons, phased execution
For larger work, the pipeline looks like this:
User Request
↓
requirement-analyzer → scope + scale
↓
technical-designer → ADR + Design Doc with acceptance criteria
↓
task-decomposer → atomic tasks (1 task = 1 commit)
↓
task-executor → TDD implementation per task
↓
quality-fixer → lint, test, build — all green
↓
Verified and ready to commit
Each subagent runs in a fresh context. The task-executor doesn't inherit assumptions from the designer. The quality-fixer rejects incomplete work before anything gets committed. By the time you look at the result, verification is already done.
Recipes
$recipe-implement Full feature lifecycle with layer routing
$recipe-task Single task with rule selection
$recipe-design Requirements → ADR / Design Doc
$recipe-diagnose Problem investigation → verified solution
$recipe-reverse-engineer Generate docs from existing code
Frontend and fullstack recipes are included for React/TypeScript projects.
Context separation
Generation and verification happen in separate agent contexts. The document-reviewer doesn't know what the technical-designer was thinking — it reviews the output cold. The investigator collects evidence without confirmation bias from whoever reported the bug. This is context engineering, not prompt engineering.
Setup
cd your-project
npx codex-workflows install
Works with GPT-5.4, GPT-5.3-Codex, and GPT-5.3-Codex-Spark. Agents are configured via TOML files — model, sandbox mode, skills, and instructions are all editable per agent.
Codex-native counterpart of claude-code-workflows.
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