Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add longranger2/claude-gpt-workflow --skill plan-executegit clone --depth 1 https://github.com/longranger2/claude-gpt-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-execute)<a href="https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-execute"><img src="https://agentmods.dev/badge/skills/longranger2/claude-gpt-workflow/plan-execute/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-execute"><img src="https://agentmods.dev/badge/skills/longranger2/claude-gpt-workflow/plan-execute.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01370 |
| Opus 5.5 | $0.00025 | $0.00548 |
| Sonnet 5.5 | $0.00012 | $0.00274 |
| Haiku 4.5 | $0.00006 | $0.00137 |
Grade A, and why
plan-execute scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Execute Skill
Purpose
When the user runs /plan-execute {plan-file-path}, start the "orchestrated plan execution" workflow:
- I (Claude Code) ask Codex to implement the code according to the plan.
- After Codex finishes, I review the generated code.
- I write the review into the
reviews/directory, then ask Codex to inspect and fix the issues. - 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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 153 lines · 62 tokens per session scan A 3b57c8a65e58
plan-execute is a skill published in the GitHub repository longranger2/claude-gpt-workflow (81 stars, last pushed 4mo ago), licensed MIT. It adds 62 tokens to every session and 1,370 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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