Claude Codex Memory Sync — Development skill for Claude Code
Lightweight local one-way memory sync from Claude Code to Codex for Windows PowerShell 5.1.
How to install Claude Codex Memory Sync
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open DaizeDong/claude-codex-memory-sync and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Claude Codex Memory Sync does
Lightweight local one-way memory sync from Claude Code to Codex for Windows PowerShell 5.1.
Alternatives in Development
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- App It — A Claude Code + Codex skill that turns a local project into a macOS Dock-launchable app — native window, its o 218 ★
README
Claude Code → Codex Memory Sync
Convert Claude Code project auto-memory into local Codex `ad_hoc` staging notes with one PowerShell command.
[](https://github.com/DaizeDong/claude-codex-memory-sync/actions/workflows/test.yml) [](sync-claude-memory-to-codex.ps1) [](LICENSE) [](#languages)
[English](README.md) | [中文版](README_CN.md)
This is an independent community project. It is not affiliated with or endorsed by Anthropic or OpenAI.
⭐ Read this first: the design philosophy
**Stage verifiable memory updates; never pretend the two agents share a brain.**
This tool is intentionally small. Its design follows three principles:
- Fill the seam, do not add another agent surface. Claude Code already stores project memory, and Codex already owns its memory consolidation. This tool only converts one representation into the format accepted by the detected local ingress contract. It adds no agent terminal, daemon, MCP server, database, vector store, or model call.
- Stage through the detected local contract, do not impersonate Codex internals. The script appends self-contained notes under
extensions\ad_hoc\notes\. It never rewrites Codex memory summaries, rollout evidence, or SQLite state. A successful sync means “safely staged,” not “already consolidated or guaranteed to be recalled.” - Memory quality matters more than memory volume. Dry-run first, select conservatively, fail closed on likely credentials, bound every input, and deduplicate incrementally. Copying every log and stale decision would make the pool larger while potentially making recall worse.
The design target is the smallest audit
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