codex-cli-bridge

Name: codex-cli-bridge
Author: tomevault-io

AI Community

Repo stars 0
Author updated Live
Author repo skills-registry

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: AI
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @tomevault-io · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: Python
Permissions: Read-only
Write / modify
Shell exec
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview codex-cli-bridge.preview

---
name: codex-cli-bridge
description: Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides C…
category: ai
runtime: Python
---

# codex-cli-bridge output preview

## PART A: Task fit
- Use case: Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Purpose / Key Capabilities / 1. CLAUDE.md → AGENTS.md Generation” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “Purpose / Key Capabilities / 1. CLAUDE.md → AGENTS.md Generation” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: codex-cli-bridge
description: Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides C…
category: ai
source: tomevault-io/skills-registry
---

# codex-cli-bridge

## When to use
- Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution hel…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “Purpose / Key Capabilities / 1. CLAUDE.md → AGENTS.md Generation” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "codex-cli-bridge" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Purpose / Key Capabilities / 1. CLAUDE.md → AGENTS.md Generation
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Python | read files, write/modify files, run shell commands | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Purpose”, “Key Capabilities”, “1. CLAUDE.md → AGENTS.md Generation”, “2. Safety Mechanism”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name codex-cli-bridge directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Purpose / Key Capabilities / 1. CLAUDE.md → AGENTS.md Generation” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write / shell-exec; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Codex CLI Bridge Skill

Purpose

This skill creates a comprehensive bridge between Claude Code and OpenAI's Codex CLI, enabling seamless interoperability through:

Documentation Translation: Converts CLAUDE.md → AGENTS.md (reference-based, no file duplication)
Execution Helpers: Python wrappers for Codex CLI commands (always uses codex exec)
Skill Documentation: Makes Claude Skills accessible to Codex CLI users

Key Capabilities

1. CLAUDE.md → AGENTS.md Generation

Parses CLAUDE.md and project structure
Scans .claude/skills/, .claude/agents/, documentation/ folders
Generates comprehensive AGENTS.md with file path references
Reference-based: No file duplication, only links to existing files
Documents Skills with most relevant usage method (bash scripts vs prompt references)

2. Safety Mechanism

Auto-checks Codex CLI installation (codex --version)
Auto-runs /init if CLAUDE.md missing (with user notification)
Validates authentication and environment
User-friendly error messages

3. Codex CLI Execution Helpers

exec_analysis() - Read-only analysis tasks (gpt-5, read-only sandbox)
exec_edit() - Code editing tasks (gpt-5-codex, workspace-write)
exec_with_search() - Web search-enabled tasks
resume_session() - Continue last Codex session
Always uses codex exec (never plain codex - critical for Claude Code)

4. Skill Documentation for Codex CLI

Prompt-only skills: Show how to reference in Codex prompts
Functional skills: Show how to execute Python scripts directly
Complex skills: Show both methods
Includes proper codex exec command syntax
Model selection guidance (gpt-5 vs gpt-5-codex)

Input Requirements

For AGENTS.md Generation

{
  "action": "generate-agents-md",
  "project_root": "/path/to/project",
  "options": {
    "validate_codex": true,
    "auto_init": true,
    "include_mcp": true,
    "skill_detail_level": "relevant"
  }
}

For Codex Execution

{
  "action": "codex-exec",
  "task_type": "analysis|edit|search",
  "prompt": "Your task description",
  "model": "gpt-5|gpt-5-codex",
  "sandbox": "read-only|workspace-write|danger-full-access"
}

Output Formats

AGENTS.md Structure

# AGENTS.md

## Project Overview
[From CLAUDE.md]

## Available Skills
### Skill Name
**Location**: `path/to/skill/`
**Using from Codex CLI**: [Most relevant method]

## Workflow Patterns
[Slash commands → Codex equivalents]

## MCP Integration
[MCP server references]

## Command Reference
| Claude Code | Codex CLI |
|-------------|-----------|
[Mappings]

Execution Helper Output

{
  "status": "success|error",
  "output": "Command output",
  "session_id": "uuid",
  "model_used": "gpt-5|gpt-5-codex",
  "command": "codex exec ..."
}

Python Scripts

safety_mechanism.py

Check Codex CLI installation
Validate CLAUDE.md exists (auto-run /init if missing)
Environment validation
User notifications

claude_parser.py

Parse CLAUDE.md sections
Scan skills, agents, commands
Extract quality gates and MCP configuration
Return file paths only (no content duplication)

project_analyzer.py

Auto-detect project structure
Discover all Claude Code assets
Generate project metadata
Build reference map

agents_md_generator.py

Template-based AGENTS.md generation
File path references (no duplication)
Skill documentation (most relevant method)
Workflow translation (Claude → Codex)

skill_documenter.py

Document skills for Codex CLI users
Determine most relevant usage method per skill type
Generate bash examples for Python scripts
Create Codex prompt templates

codex_executor.py

Python wrappers for Codex CLI commands
Intelligent model selection (gpt-5 vs gpt-5-codex)
Sandbox mode helpers
Session management
Always uses codex exec

Usage Examples

Example 1: Generate AGENTS.md

User prompt:

Generate AGENTS.md for this project

What happens:

Safety mechanism checks Codex CLI installed
Checks CLAUDE.md exists (auto-runs /init if missing)
Parses CLAUDE.md and project structure
Generates AGENTS.md with file references
Documents all skills with most relevant usage method

Output: Complete AGENTS.md file in project root

Example 2: Execute Codex Analysis Task

User prompt:

Use Codex to analyze this codebase for security vulnerabilities

What happens:

from codex_executor import CodexExecutor

executor = CodexExecutor()
result = executor.exec_analysis(
    "Analyze this codebase for security vulnerabilities",
    model="gpt-5"
)

Executes:

codex exec -m gpt-5 -s read-only \
  -c model_reasoning_effort=high \
  "Analyze this codebase for security vulnerabilities"

Example 3: Execute Codex Code Editing

User prompt:

Use Codex to refactor main.py for better async patterns

What happens:

executor = CodexExecutor()
result = executor.exec_edit(
    "Refactor main.py for better async patterns",
    model="gpt-5-codex"
)

Executes:

codex exec -m gpt-5-codex -s workspace-write \
  -c model_reasoning_effort=high \
  "Refactor main.py for better async patterns"

Example 4: Resume Codex Session

User prompt:

Continue the previous Codex session

What happens:

executor = CodexExecutor()
result = executor.resume_session()

Executes:

codex exec resume --last

Best Practices

For AGENTS.md Generation

Always run on projects with CLAUDE.md (or let auto-init create it)
Validate Codex CLI installed first
Keep skills documented with most relevant method (bash vs prompt)
Use reference-based approach (no file duplication)

For Codex Execution

Use codex exec always (never plain codex in Claude Code)
Choose correct model:
- gpt-5: General reasoning, architecture, analysis
- gpt-5-codex: Code editing, specialized coding tasks
Choose correct sandbox:
- read-only: Safe analysis (default)
- workspace-write: File modifications
- danger-full-access: Network access (rarely needed)
Enable search when needed (--search flag)

For Skill Documentation

Prompt-only skills: Reference in Codex prompts
Functional skills: Execute Python scripts directly
Complex skills: Show both methods
Always provide working examples

Command Integration

This skill integrates with existing Claude Code commands:

/init: Auto-generates AGENTS.md after CLAUDE.md creation
/update-claude: Regenerates AGENTS.md when CLAUDE.md changes
/check-docs: Validates AGENTS.md exists and is in sync
/sync-agents-md: Manual AGENTS.md regeneration
/codex-exec <task>: Wrapper using codex_executor.py

Installation

Prerequisites

Codex CLI installed:

codex --version  # Should show v0.48.0 or higher

Codex authenticated:
```
codex login
```
Claude Code v1.0+

Install Skill

Option 1: Copy to project

cp -r generated-skills/codex-cli-bridge ~/.claude/skills/

Option 2: Use from this repository

# Skill auto-discovered when Claude Code loads this project

Troubleshooting

Error: "Codex CLI not found"

Solution: Install Codex CLI and ensure it's in PATH

which codex  # Should return path
codex --version  # Should work

Error: "CLAUDE.md not found"

Solution: Skill auto-runs /init with notification. If it fails:

# Manually run /init
/init

Error: "stdout is not a terminal"

Solution: Always use codex exec, never plain codex

❌ codex -m gpt-5 "task"
✅ codex exec -m gpt-5 "task"

AGENTS.md Out of Sync

Solution: Regenerate manually

/sync-agents-md

References

Codex CLI Docs: openai-codex-cli-instructions.md
Claude Skills Docs: claude-skills-instructions.md
Example Skills: claude-skills-examples/codex-cli-skill.md
AGENTS.md Spec: https://agents.md/

Version

v1.0.0 - Initial release (2025-10-30)

License

Apache 2.0

Created by: Claude Code Skills Factory Maintained for: Cross-tool team collaboration (Claude Code ↔ Codex CLI) Sync Status: Reference-based bridge (one-way sync: CLAUDE.md → AGENTS.md)

Source: ComeOnOliver/skillshub — distributed by TomeVault.

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add tomevault-io/skills-registry/comeonoliver--skillshub--codex-cli-bridge -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

未声明 license/许可。
未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
tomevault-io/skills-registry
中文

More by @tomevault-io

Category & tags

Category AI

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

Codex CLI Bridge Skill

Purpose

Key Capabilities

1. CLAUDE.md → AGENTS.md Generation

2. Safety Mechanism

3. Codex CLI Execution Helpers

4. Skill Documentation for Codex CLI

Input Requirements

For AGENTS.md Generation

For Codex Execution

Output Formats

AGENTS.md Structure

Execution Helper Output

Python Scripts

safety_mechanism.py

claude_parser.py

project_analyzer.py

agents_md_generator.py

skill_documenter.py

codex_executor.py

Usage Examples

Example 1: Generate AGENTS.md

Example 2: Execute Codex Analysis Task

Example 3: Execute Codex Code Editing

Example 4: Resume Codex Session

Best Practices

For AGENTS.md Generation

For Codex Execution

For Skill Documentation

Command Integration

Installation

Prerequisites

Install Skill

Troubleshooting

Error: "Codex CLI not found"

Error: "CLAUDE.md not found"

Error: "stdout is not a terminal"

AGENTS.md Out of Sync

References

Version

License

Discussion