cloud-alter-ego

Your cloud alter ego for AI coding agents. It remembers what you did yesterday, on which laptop, with which account, and makes every agent follow your rules.

cloud-alter-ego is a Git repo that becomes the shared memory of every agent you work with: Claude Code on any account and any device (including Remote Control from your phone) and Codex. Hooks inject your working rules at the start of every session, log every question and answer into a journal per client or project, save full transcripts at the end, and push it all, so every device and account always works from the same brain.

you ask something ──> UserPromptSubmit hook ──> journal line ──> git push
agent answers     ──> Stop hook             ──> journal line ──> git push
new session       ──> SessionStart hook     ──> your rules + active client injected
session ends      ──> SessionEnd hook       ──> full transcript saved ──> git push
another device    ──> git pull on start     ──> same memory everywhere

Repo or connector

There are two ways to get the same memory:

• This repo is for people who work with Claude Code or Codex on their own machines. Hooks log every turn, save transcripts and inject your rules without the agent having to remember anything.
• The Alter Ego connector, a remote MCP server, is for chats in Claude or ChatGPT, on the web or the phone, without installing anything. It keeps the memory in your own OneDrive, Google Drive, Dropbox, GitHub or Azure DevOps.

They work together: point the connector at the GitHub or Azure DevOps copy of this repo and it reads preferences.md, identity.md, clients/, projects/ and skills/ as they are, and writes journal lines in the same format.

Get started

1. Make your own private copy. Click Use this template on GitHub and choose Private. Your copy will fill up with clients, conversations and journals. Never make it public.

2. Clone it anywhere on your machine.

3. Install: python tools/install.py (Python 3.8+ and git needed). It registers the hooks in every Claude Code config it finds, adds a pointer to your global CLAUDE.md, turns off AI attribution in commits and, when Codex is installed, hooks Codex in too. Settings files are backed up first. Undo with python tools/install.py --uninstall.

4. Start a new Claude Code session. Your rules are injected automatically from now on.

5. Make it yours: fill in identity.md, tune preferences.md, and add your work:

   python tools/note.py --new-client acme
   python tools/note.py --new-project my-app
   

   Tip: ask your agent to go through all your GitHub repos (gh repo list) and create a project folder for each, so nothing is missing from day one.

6. Every other device or account: clone the same private repo and run the installer there.

What is in the box

The core is five hooks and note.py, all plain Python with no dependencies, on Windows, macOS and Linux. Everything else is optional: take what fits your work.

Core

Path	What
preferences.md	Working rules injected at every session start. Sensible defaults for style, scope, code and facts; edit them
preferences-background.md	The reasoning behind every rule
identity.md	Who you are: role, stack, how you work with agents (template)
personal.md	Optional personal context (template)
clients/	One folder per client: README with stack and incident history, journal/, sessions/
projects/	One folder per own project, plus the infrastructure they share
WORKFLOW.md	How the hooks, contexts and syncing work
tools/install.py	Registers the hooks, undo with --uninstall
tools/session_start.py, auto_journal.py, save_session.py, block_ai_attribution.py	The hooks: inject rules, log every turn, save the transcript, block AI attribution
tools/note.py	Journal lines and contexts
tools/redact.py	Masks tokens, keys and passwords in every journal line and saved transcript before it is pushed
tests/	python -m pytest -q tests
CHANGELOG.md	What changed per release

Optional

Path	What
skills/	Runbooks. Core ones for how agents work for you, plus examples from real work (data platforms, client tickets, sales, investing) to keep, delete or copy
techniques/	Reusable technical knowledge: Fabric, fabric-cicd, dbt, Databricks, Azure, Entra ID, Microsoft 365 groups, Power BI, Git, client environments, agent sessions on a Linux server
tools/run_routine.sh, run_routine.ps1	Scheduled routines with a fixed session and usage-limit recovery
tools/token_usage.py	Token use per session
tools/firefox_profile.py	Signed-in browser access through a copy of a Firefox profile
tools/*.ps1	Windows only: start and watch Remote Control sessions, type into a session, start ChatGPT
tools/server/	Linux with systemd: agent sessions on a small server

Daily use

• Tell the agent what you are working on, or set it yourself: python tools/note.py --set acme. The context is per session, so parallel sessions each log to their own journal. The agent reads that client's README and newest journal before it starts.
• The agent writes one meaningful journal line per turn. The automatic lines from the hooks are a safety net, the agent's line is the summary a future session needs.
• When a session teaches you something reusable, it goes into techniques/. A new working rule goes into preferences.md, with the story behind it in preferences-background.md.

Privacy and safety

• Your copy must be private: transcripts and journals are pushed automatically. The installer warns when your remote is public.
• Never store secrets here. Resource names are fine, keys and passwords are not. As a safety net tools/redact.py masks known token formats, private keys and password=-style values in journals and transcripts. It does not catch everything, so still keep secrets out of chats.
• .current-context, .current-context.d/, .auto-journal/ and tools/sessions.json are local and gitignored.
• The hooks never fail hard: errors go to .auto-journal/errors.log and a session never gets stuck.
• Journals use a union merge (.gitattributes), so parallel sessions never block each other on a journal conflict.

Requirements

• Claude Code (any plan that supports hooks), optionally Codex.
• Python 3.8 or newer, git, and a private Git remote.
• Windows, macOS or Linux for the core. See Optional above for the parts tied to one system.

License

MIT, see LICENSE.