Plan first. Run Codex with clear approvals and full visibility.
See impacted files, generate and merge multi-model plans, then execute Codex CLI with approval modes that match your governance needs.
PlanToCode provides the planning layer with file discovery and multi-model synthesis. You review file-by-file specs, then run Codex with Auto (default), Read-Only, or Full Access approval modes.
$5 free credits • Pay-as-you-go • Works with all major AI coding tools
This page shows how PlanToCode's reviewable, file-by-file implementation specs integrate with OpenAI Codex CLI, with all claims verified against official documentation.
What PlanToCode gives you here
Human-in-the-loop governance
Maintain full control over AI-generated implementation plans. Review proposed changes, edit plan details, and approve before execution. Every step is visible, auditable, and aligned with your requirements.
File-by-file plans with exact repository paths
Implementation plans break down changes on a file-by-file basis with exact paths corresponding to your project structure. This granular approach ensures complete visibility into what will be modified.
Intelligent file discovery
Surface the right files before writing prompts. The file discovery workflow uses pattern groups, relevance scoring, and staged reviews to identify exactly which files your AI needs.
Integrated terminal with CLI detection
Launch AI coding CLIs directly in the built-in terminal without leaving your workspace. Health monitoring, auto-recovery, and resize handling keep long-running jobs stable.
Persistent sessions and logs
Terminal output is stored locally, and project sessions reload on startup. Close the application and return days later to pick up exactly where you left off.
Privacy and local storage
All sessions are stored locally on your machine in SQLite. When you use AI features, you see exactly what will be sent to AI providers before confirming. No hidden data collection.
How it works with this tool
Run Codex CLI from integrated terminal
Launch Codex CLI directly in PlanToCode's built-in terminal. Access your file discovery results and implementation plans while Codex runs.
Codex approval modes
Codex CLI offers three approval modes: Auto (default - workspace freedom with approval required outside workspace), Read-Only (requires approval for all file actions), and Full Access (no approvals). Choose the mode that matches your governance needs.
Windows and WSL support
Windows users run Codex CLI in WSL. PlanToCode's integrated terminal provides persistent logging and session management across WSL sessions.
File-by-file specifications
PlanToCode generates file-by-file implementation plans with exact repository paths. Review these specs before running Codex CLI to ensure all impacted files are considered.
Quickstart
- 1Install PlanToCode
Download the desktop app and connect it to your development workspace.
- 2Discover relevant files
Run file discovery to identify which files Codex will need to consider for your task.
- 3Generate and merge multi-model plans
Create implementation plans from multiple AI models and merge them with custom instructions into a comprehensive specification.
- 4Run Codex with approvals
Open Codex CLI in PlanToCode's integrated terminal. Choose your approval mode (Auto, Read-Only, or Full Access) and execute the plan.
Verified from official sources
Codex CLI is OpenAI's official command-line tool for AI-assisted coding.
Official docsCodex CLI supports three approval modes controlled via the /approvals command: Auto (default), Read-Only, and Full Access.
Official docsWindows users can run Codex CLI in WSL (Windows Subsystem for Linux) for full compatibility.
Official docsCodex CLI uses GPT-5-Codex as its default model for code generation.
Official docsCodex CLI traverses workspace files automatically to build context for code generation tasks.
Official docsFrequently Asked Questions
Everything you need to know about PlanToCode
Ready to get started?
Plan software changes before you code. Review scope, merge multi-model insights, and execute with full visibility.