Datafooding

이 Mac에 Datafooding을 설치하고, 내가 고른 AI 에이전트의 다음 세션부터 전용 GCS로 자동 백업되게 끝까지 설정해줘.

The outcome I want
- Local session files remain the source of truth and are never deleted.
- Eligible bytes are encrypted on this Mac before upload.
- Only ciphertext is stored in a dedicated bucket in my Google Cloud project.
- Existing history is excluded. Only files created or changed after the new-only baseline may be captured.
- A macOS LaunchAgent keeps capture and sync running every 15 minutes.

Exact release contract
- Version: 0.2.1
- Wheel: https://datafooding.ai/releases/datafooding_agent_vault-0.2.1-py3-none-any.whl
- SHA-256: ba21b23f23a25850adc649a3e48d78c0a8a346193546c8cfbaf63c35dae6247b
- PEP 508 target: datafooding-agent-vault @ https://datafooding.ai/releases/datafooding_agent_vault-0.2.1-py3-none-any.whl#sha256=ba21b23f23a25850adc649a3e48d78c0a8a346193546c8cfbaf63c35dae6247b

Run this workflow

1. Preflight this Mac without reading session content.
   - Confirm the OS is macOS.
   - Detect only the existence and filesystem metadata of supported stores: Codex, archived Codex, Claude Code, Hermes, Kimi Code, OpenCode, and Gemini CLI.
   - Do not open or print prompts, messages, tool results, credentials, tokens, request dumps, hidden reasoning, or session payloads.

2. Install only missing prerequisites from their official distribution.
   - Homebrew is the package manager. If it is missing, use the official brew.sh installer and no third-party mirror.
   - Install uv with Homebrew when missing.
   - Install Google Cloud CLI with the current Homebrew cask: `brew install --cask gcloud-cli`.
   - Resolve gcloud with `command -v gcloud`; if the cask is installed but PATH has not refreshed, use `$(brew --prefix)/share/google-cloud-sdk/bin/gcloud` after checking that it is executable.
   - Never use a service account, create broad IAM grants, write credentials to the repository, or put secrets in command arguments or chat.

3. Establish the Google Cloud identity interactively.
   - Check the active account and project without printing tokens. If login is required, use `gcloud auth login`.
   - Never guess a project. If none is active, ask me for the exact project ID.
   - Resolve its numeric project number with `gcloud projects describe PROJECT_ID --format='value(projectNumber)'`.
   - Propose the dedicated bucket `datafooding-PROJECT_NUMBER`.

4. Ask for one compact approval before creating cloud resources or enabling capture.
   Show one block containing:
   - the detected agent names, with nothing selected by default;
   - the exact account and project ID, redacted where appropriate;
   - the proposed bucket;
   - for a new bucket, the GCS location I must choose because it is immutable;
   - for an existing bucket, its current location and any protection change needed;
   - every local prerequisite you installed.
   Ask me to reply with the exact sources and `APPROVE`. Treat that answer as consent only for those sources, that project, that bucket, and that location.

5. Create or verify the dedicated bucket, fail closed, and never delete it.
   - First run describe. Only an explicit not-found result permits creation. A permission error, timeout, disabled API, billing problem, or ambiguous result must stop with a concrete remediation.
   - Create a missing bucket with this exact protection shape:
     `gcloud storage buckets create gs://BUCKET --project=PROJECT_ID --location=LOCATION --uniform-bucket-level-access --public-access-prevention --soft-delete-duration=7d --quiet`
   - Never set or lock an irreversible retention policy.
   - Reuse an existing bucket only when describe proves that its project number matches the selected project and its location matches the approved plan.
   - Before continuing, re-describe and verify: exact name, project number, location, uniform bucket-level access enabled, public access prevention enforced, and soft-delete retention greater than zero. If an existing bucket needs a protection update, the approval block must name it before running any update.

6. Install the exact hash-pinned Datafooding release.
   Run:
   `uv tool install --force 'datafooding-agent-vault @ https://datafooding.ai/releases/datafooding_agent_vault-0.2.1-py3-none-any.whl#sha256=ba21b23f23a25850adc649a3e48d78c0a8a346193546c8cfbaf63c35dae6247b'`
   Then require `datafooding --version` to report 0.2.1.

7. Bind only the approved sources from now.
   - Run `datafooding quickstart --plan --bucket gs://BUCKET --source SOURCE ...`.
   - Verify the content-free plan exactly matches the approved bucket and source list, says `capture_policy: new-only`, `existing_sessions_included: false`, and enables automatic capture.
   - Never use `--include-existing`, `archive-home`, or a history migration in this workflow.
   - If the plan matches, run the same quickstart command with `--yes`.

8. Trigger and verify local-to-remote sync.
   - Run `datafooding sync --capture-enabled`, then `datafooding doctor` and `datafooding status`.
   - If the active setup session changes after the baseline, it may become eligible. Let the daemon retry a file that is still changing; do not weaken the stability checks.
   - Open `datafooding admin --language ko` in a separate terminal because the local admin intentionally stays in the foreground.

9. Call setup complete only when all of these are true.
   - Doctor passes.
   - Every approved source is enabled with the new-only policy.
   - The LaunchAgent is installed, loaded, and bound to the current CLI.
   - GCS access and recoverability checks pass.
   - Queued ciphertext is zero.
   If no post-baseline file has changed yet, report `READY — waiting for the first new session`; do not claim that a session was uploaded.

Failure and rollback rules
- Stop on any identity, project, billing, ownership, location, policy, hash, or health ambiguity. Never retry with wider permissions.
- If quickstart fails after enabling a source that was off before this workflow, disable only that newly enabled source and stop the LaunchAgent started by this workflow. Preserve any pre-existing enabled source and daemon.
- Keep the local vault, Keychain entry, and protected bucket as resumable state. Do not delete source files, vault data, recovery material, or cloud objects.
- Return a short content-free receipt: version, selected source names, bucket protection status, capture policy, LaunchAgent state, queue count, and the exact next remediation if anything is incomplete.