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Plan Execute

Community
longranger2
plan-execute

Use when the user says "/plan-execute", "plan execute", "implement plan", or "execute plan" and provides a finalized plan file path to carry out. Claude orchestrates, Codex writes code, Claude reviews, and Codex fixes issues until the quality bar is met.

Overview

Publisherlongranger2
Repositoryclaude-gpt-workflow
Skill nameplan-execute
Stars
81
Forks
12
Bundled files
Instructions only
LicenseMIT
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 longranger2 on GitHub. Read the source before you install it.

Installation

Install the Plan Execute 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.
    https://github.com/longranger2/claude-gpt-workflow/tree/main/plan-execute
  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/longranger2/claude-gpt-workflow.git /tmp/claude-gpt-workflow
mkdir -p .claude/skills
cp -r /tmp/claude-gpt-workflow/plan-execute .claude/skills/plan-execute
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Execute 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 Plan Execute 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 Plan Execute 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.

Plan Execute Skill

Purpose

When the user runs /plan-execute {plan-file-path}, start the "orchestrated plan execution" workflow:

  1. I (Claude Code) ask Codex to implement the code according to the plan.
  2. After Codex finishes, I review the generated code.
  3. I write the review into the reviews/ directory, then ask Codex to inspect and fix the issues.
  4. Repeat until the code quality bar is met.

Core principle: I do not write or edit code myself. I only do two things: review code and orchestrate Codex. All code changes, including implementation and fixes, are performed by Codex.

Usage

/plan-execute plans/my-feature-plan.md

Session Reuse

After each Codex invocation, extract session_id=xxx from the script output and save it as the session ID for the current task. In later Codex calls for the same task, pass --session <id> to reuse context so Codex remembers prior implementation and fix history instead of rereading the entire codebase every time.

My Workflow (Claude Code)

Step 1: Read the Plan and Split Execution Steps

Read the specified plan file and understand:

  • The overall goal and scope of the plan
  • The list of files to create or modify
  • The order of implementation steps
  • Relevant project conventions, especially from CLAUDE.md

If the plan already contains a checklist (- [ ] / - [x]), use those items as execution units. If it does not define clear steps, split the work into reasonable batches, with no more than 5 file changes per batch.

Step 2: Ask Codex to Implement the Code

Use the /codex skill and give Codex the following instruction:

Implement the code according to the plan in {plan-file-path}.

Current execution scope: {specific step or batch description}

Requirements:
- Follow the design in the plan exactly. Do not improvise beyond it.
- Obey the Code Quality Hard Limits defined in `CLAUDE.md`.
- Single file <= 800 lines, single function <= 50 lines, nesting <= 3 levels
- Run `pnpm build` after implementation to confirm compilation succeeds
- If the plan includes a checklist, mark completed steps as `[x]`

After implementation, list all changed files and provide a summary of each change.

Step 3: Review Codex Output (My Core Responsibility)

After Codex finishes, I perform a code review. Important: I only read code and write reviews. I never directly modify source files.

  1. Read every changed file and review them one by one.
  2. Compare against the plan to verify the implementation matches the intended design.
  3. Check code quality, including:
    • Whether it violates the Code Quality Hard Limits
    • Whether it introduces security risks
    • Whether error handling is missing
    • Whether naming and organization are clear
    • Whether it follows existing project patterns
  4. Run pnpm build to confirm the compilation status.

Step 4: Write the Review and Hand Fixes Back to Codex

Append the review to reviews/{topic}-review.md (shared with plan-review):

markdown
---

## Code Review Round {N} — {YYYY-MM-DD}

**Scope**: {code scope covered in this review}
**Build Status**: PASS / FAIL

### Issues

#### Issue 1 ({severity}): {title}
**File**: {file-path:line}
{issue description}
**Fix**: {specific fix recommendation}

...

### Verdict: NEEDS_FIX / APPROVED

If Verdict: NEEDS_FIX, call /codex and have Codex fix the issues instead of editing them myself:

Read the latest Code Review round in {review-file-path}.
Check each issue one by one. Fix the valid issues, and explain why any disputed item is not actually a problem.
After making fixes, run `pnpm build` to confirm compilation succeeds.
List the issues that were fixed and the corresponding code changes.

If Verdict: APPROVED, skip to Step 6.

Step 5: Verify Fixes and Iterate

After Codex applies fixes, I review again, still without editing code directly:

  • Check whether each issue was truly fixed
  • Check whether the fixes introduced new problems
  • If issues remain, write a new review round and hand it back to Codex for another fix pass (repeat Step 4)
  • If everything passes, mark the review as Verdict: APPROVED

Step 6: Update Plan Progress

After each batch is completed, ask Codex to update the checklist in the plan file (- [ ] -> - [x]). If unfinished steps remain, go back to Step 2 for the next batch. Once all work is complete, move to the wrap-up.

Step 7: Wrap Up

Report the following to the user:

  • Which steps were completed
  • How many code review rounds were needed
  • Which major issues were fixed
  • Final build status
  • List of changed files
  • Path to the review log file

Review Severity Levels

LevelMeaningMust Fix
CriticalCauses runtime failures or security vulnerabilitiesYes
HighViolates project conventions or has obvious design flawsYes
MediumCode quality issue that should be improvedRecommended
LowStyle or preference issueOptional
SuggestionOptimization suggestionOptional

Verdict rules:

  • If any Critical or High issue exists -> NEEDS_FIX
  • If all issues are Medium or below -> APPROVED with optional improvement notes

File Convention

  • Share the same review file as plan-review: reviews/{topic}-review.md
  • {topic} is the plan file name without .md
  • Both plan review rounds and code review rounds are appended to the same file
  • Distinguish them by heading: ## Round {N} for plan review and ## Code Review Round {N} for code review

Frequently asked questions

What does the Plan Execute AI skill do?

Use when the user says "/plan-execute", "plan execute", "implement plan", or "execute plan" and provides a finalized plan file path to carry out. Claude orchestrates, Codex writes code, Claude reviews, and Codex fixes issues until the quality bar is met.

Why use Plan Execute on TypingMind?

Because you install it once and use it with any model. Plan Execute 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 Plan Execute in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/longranger2/claude-gpt-workflow/tree/main/plan-execute. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan Execute?

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 Plan Execute?

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

Is the Plan Execute AI skill free?

Yes. It is published on GitHub by longranger2 under the MIT license. 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.

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