Codex Claude Cursor Loop logo

Codex Claude Cursor Loop

Community
bear2u
codex-claude-cursor-loop

Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality

Overview

Publisherbear2u
Repositorymy-skills
Skill namecodex-claude-cursor-loop
Stars
932
Forks
210
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bear2u on GitHub. Read the source before you install it.

Installation

Install the Codex Claude Cursor Loop AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bear2u/my-skills.git /tmp/my-skills
mkdir -p .claude/skills
cp -r /tmp/my-skills/skills/codex-claude-cursor-loop .claude/skills/codex-claude-cursor-loop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex Claude Cursor Loop in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Codex Claude Cursor Loop on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Codex Claude Cursor Loop is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Codex-Claude-Cursor Engineering Loop Skill

Core Workflow Philosophy

This skill implements a 3-way sequential validation engineering loop:

  • Claude Code: Architecture and planning, final review
  • Codex: Plan validation (logic/security), code review (bugs/performance)
  • Cursor Agent: Code implementation and execution
  • Sequential Validation: Claude plans → Codex validates → Cursor implements → Codex reviews → Claude final check → repeat

Phase 1: Planning with Claude Code

  1. Start by creating a detailed plan for the task
  2. Break down the implementation into clear steps
  3. Document assumptions and potential issues
  4. Output the plan in a structured format

Phase 2: Plan Validation with Codex

  1. Ask user (via AskUserQuestion):
    • Model: gpt-5 or gpt-5-codex
    • Reasoning effort: low, medium, or high
  2. Send the plan to Codex for validation:
bash
   echo "Review this implementation plan and identify any issues:
   [Claude's plan here]

   Check for:
   - Logic errors
   - Missing edge cases
   - Architecture flaws
   - Security concerns" | codex exec -m <model> --config model_reasoning_effort="<effort>" --sandbox read-only
  1. Capture Codex's feedback and summarize to user

Phase 3: Plan Refinement Loop

If Codex finds issues in the plan:

  1. Summarize Codex's concerns to the user
  2. Refine the plan based on feedback
  3. Ask user (via AskUserQuestion): "Should I revise the plan and re-validate, or proceed with implementation?"
  4. Repeat Phase 2 if needed until plan is solid

Phase 4: Implementation with Cursor Agent

Once the plan is validated by Codex:

Session Management

  1. Ask user (via AskUserQuestion): "Do you want to start a new Cursor session or resume an existing one?"

    • New session: Start fresh
    • Resume session: Continue previous work
  2. If resuming:

bash
   # List available sessions
   cursor-agent ls

   # Let user select session ID
   # Store session ID for subsequent calls
  1. Ask user (via AskUserQuestion): Which Cursor model to use (e.g., composer-1, claude-3.5-sonnet, gpt-4o)

Implementation

  1. Send the validated plan to Cursor Agent:

For new session:

bash
   cursor-agent --model "<model-name>" -p --force "Implement this plan:
   [Validated plan here]

   Please implement the code following these specifications exactly."

For resumed session:

bash
   cursor-agent --resume="<session-id>" -p --force "Continue implementation:
   [Validated plan here]"
  1. IMPORTANT: Store the session ID from the output for all subsequent Cursor calls
  2. Capture what was implemented and which files were modified

Phase 5: Codex Code Review

After Cursor implements:

  1. Send Cursor's implementation to Codex for code review:
bash
   echo "Review this implementation for:
   - Bugs and logic errors
   - Performance issues
   - Security vulnerabilities
   - Best practices violations
   - Code quality concerns

   Files modified: [list of files]
   Implementation summary: [what Cursor did]" | codex exec --sandbox read-only
  1. Capture Codex's code review feedback
  2. Summarize findings to user

Phase 6: Claude's Final Review

After Codex code review:

  1. Claude reads the implemented code using Read tool
  2. Claude analyzes both:
    • Codex's review findings
    • The actual implementation
  3. Claude provides final assessment:
    • Verify if it matches the original plan
    • Confirm Codex's findings are valid
    • Identify any additional concerns
    • Make final architectural decisions
  4. Summarize overall quality and readiness

Phase 7: Iterative Improvement Loop

If issues are found (by Codex or Claude):

  1. Claude creates a detailed fix plan based on:
    • Codex's code review findings
    • Claude's final review insights
  2. Send the fix plan to Cursor Agent using the same session:
bash
   # IMPORTANT: Use --resume with the stored session ID
   cursor-agent --resume="<session-id>" -p --force "Fix these issues:
   [Detailed fix plan]

   Issues from Codex: [list]
   Issues from Claude: [list]"
  1. After Cursor fixes, repeat from Phase 5 (Codex code review)
  2. Continue the loop until all validations pass
  3. Note:
    • Use same Codex model for consistency
    • Always use the same Cursor session ID to maintain context
    • Session maintains full history of changes

Recovery When Issues Are Found

When Codex finds plan issues (Phase 2):

  1. Claude analyzes Codex's concerns
  2. Refines the plan addressing all issues
  3. Re-submits to Codex for validation
  4. Repeats until Codex approves

When Codex finds code issues (Phase 5):

  1. Claude reviews Codex's findings
  2. Creates detailed fix plan
  3. Sends to Cursor for fixes
  4. After Cursor fixes, back to Codex review
  5. Repeats until Codex approves

When Claude finds issues (Phase 6):

  1. Claude creates comprehensive fix plan
  2. Sends to Cursor for implementation
  3. After fixes, Codex reviews again
  4. Claude does final check
  5. Repeats until Claude approves

Best Practices

  • Always validate plans with Codex before implementation
  • Never skip Codex code review after Cursor implements
  • Never skip Claude's final review for architectural oversight
  • Maintain clear handoff between all three AIs
  • Document who did what for context
  • Use same models throughout (same Codex model, same Cursor model)
  • Session Management:
    • Always use --resume with same session ID for iterative fixes
    • Store session ID at the start and reuse throughout
    • Use cursor-agent ls to find previous sessions
    • Only start new session when beginning completely new feature

Command Reference

PhaseWhoCommand PatternPurpose
1. PlanClaudeTodoWrite, Read, analysis toolsClaude creates detailed plan
2. Validate planCodexecho "plan" | codex exec -m <model> --config model_reasoning_effort="<effort>" --sandbox read-onlyCodex validates logic/security
3. RefineClaudeAnalyze Codex feedback, update planClaude fixes plan issues
4. Session setupClaude + UserAsk new/resume, cursor-agent ls if neededSetup or resume Cursor session
5. ImplementCursorcursor-agent --model "<model>" -p --force "prompt" OR cursor-agent --resume="<id>" -p --force "prompt"Cursor implements validated plan
6. Review codeCodexecho "review" | codex exec --sandbox read-onlyCodex reviews for bugs/performance
7. Final reviewClaudeRead tool, analysisClaude final architectural check
8. Fix planClaudeCreate detailed fix planClaude plans fixes from all feedback
9. Apply fixesCursorcursor-agent --resume="<id>" -p --force "fixes"Cursor implements fixes in same session
10. Re-reviewCodex + ClaudeRepeat phases 6-7Validate fixes until perfect

Error Handling

  1. Monitor Cursor Agent output for errors
  2. Summarize Cursor's implementation results and Claude's review
  3. Ask for user direction via AskUserQuestion if:
    • Significant architectural changes needed
    • Multiple files will be affected
    • Breaking changes are required
  4. When issues appear, Claude creates a detailed fix plan before sending to Cursor

The Perfect Loop

1. Plan (Claude)
2. Validate Plan (Codex) → if issues → refine plan → repeat
3. Implement (Cursor)
4. Code Review (Codex) → captures bugs/performance issues
5. Final Review (Claude) → architectural check
6. Issues found? → Fix Plan (Claude) → Implement Fixes (Cursor) → back to step 4
7. All passed? → Done! ✅

This creates a triple-validation, self-correcting, high-quality engineering system where:

  • Claude: All planning, architecture, and final oversight
  • Codex: All validation (plan logic + code quality)
  • Cursor Agent: All implementation and coding

Frequently asked questions

What does the Codex Claude Cursor Loop AI skill do?

Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality

Why use Codex Claude Cursor Loop on TypingMind?

Because you install it once and use it with any model. Codex Claude Cursor Loop is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Codex Claude Cursor Loop in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bear2u/my-skills/tree/master/skills/codex-claude-cursor-loop. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Codex Claude Cursor Loop?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Codex Claude Cursor Loop?

As many as you like. As long as a model supports skills, you can use Codex Claude Cursor Loop with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Codex Claude Cursor Loop AI skill free?

It is published on GitHub by bear2u. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇