Clawdi Onboarding

Clawdi Cloud Setup

You're helping the user connect this machine to Clawdi Cloud—the best home for all their AI agents. They can run Agents in the cloud or connect their own, with context and tools in one place.

This walkthrough takes 2-3 minutes. The end state: the user's existing session history shows up at their Clawdi Cloud dashboard. If you stop earlier, the dashboard stays empty and they assume the product is broken.

Install the CLI

bun add -g clawdi

If bun isn't installed on the system, fall back to npm:

npm install -g clawdi

Verify it landed:

clawdi --version

Authenticate

The CLI hands the user a verification URL; they approve in their browser; you complete the handshake. Two phases because you can't block waiting for a browser click.

Start the authorization:

clawdi auth login

This prints a verification URL and a short user code, then exits immediately. Show both to the user in chat. Tell them: open the URL, confirm the code matches, click approve, and reply when they're done.

When they reply, finish the handshake:

clawdi auth complete

If it prints "Still waiting for approval" (exit code 2), the user hasn't clicked approve yet. Ask them to finish in the browser, then re-run clawdi auth complete. The 10-minute window starts at auth login; if it expires, restart from there.

⚠️ Don't pass --manual to auth login — that flag wants an interactive TTY password prompt and fails in agent contexts.

Register agents on this machine

clawdi setup

Auto-detects every installed AI agent (Claude Code, Codex, Hermes, OpenClaw, Pi, and OpenCode), registers each with the cloud, configures only the local modules each agent supports, and installs background sync daemons by default. Pi and OpenCode sync Sessions only; neither receives Skill or MCP installation. Without an --agent flag it picks up everything detected — which is what you want, so later sync steps can cover all of them.

Sync the user's sessions

This step fills the dashboard with the user's conversation history. Don't ask them to make a decision in the abstract — show them what's actually on their machine first, then ask. Like git status before git commit.

Scan first

clawdi session list --all-agents --all --limit 10000 --json

--limit 10000 is important — the default is 100, which would silently truncate any user with more sessions and you'd aggregate from a partial set.

If this fails (network error, no agents registered, etc.), tell the user "I couldn't list your local sessions — going ahead with the default upload, let me know if you want to stop." and skip to running clawdi push --modules sessions --all-agents --all. Don't halt onboarding for this.

If the JSON is empty ([]), tell the user "No sessions found on this machine — nothing to sync. Run clawdi push later if you start using one of the supported agents." and continue to the next step. Skip the upload entirely.

Show a bounded summary, then ask

Parse the JSON locally. Group by agent, then by project. Count sessions per project. Sort by count descending.

Cap the displayed projects per agent at top 5. A user with 100 active projects would otherwise produce a 100-line wall of text that buries the question. If there are more than 5, append a single …and N more projects line so they know the list is truncated. Always state the per-agent total counts (sessions and projects) so the scale is visible.

Render something like (use the user's actual paths and counts, not these numbers):

I found 215 sessions on this machine:

Claude Code (180 sessions across 47 projects):

• ~/work/clawdi — 23 sessions
• ~/work/client-acme — 18 sessions
• ~/personal/blog — 12 sessions
• ~/work/api-gateway — 9 sessions
• ~/scratch — 7 sessions
• …and 42 more projects

Codex (35 sessions across 8 projects):

• ~/work/clawdi — 11 sessions
• ~/work/client-acme — 8 sessions
• ~/work/api-gateway — 6 sessions
• ~/personal/blog — 5 sessions
• ~/scratch — 3 sessions
• …and 3 more projects

Want me to upload all of them to your Clawdi Cloud dashboard? Or are there any projects you'd rather skip — anything client-confidential, NDA work, etc.?

Reply y to upload all, or name any projects to skip (works for projects not in the list above too).

The closing line about "not in the list above too" is important: the cap might hide a low-session-count NDA repo the user actually cares about excluding. Accept any project path they name, listed or not.

Translate the answer to a push command

The user references real project names from the summary you just showed them. Match their reply to a command:

Resolve ~ to an absolute path before passing to the CLI.

Note the "X new, Y updated, Z unchanged" total from the push output — you'll cite it next.

Verify live sync (recommended)

clawdi setup installs the sync daemon by default. Connected Skills sync from the Agent and are managed there. For Hosted managed Workspace Skills, the dashboard can request installation or removal, while the runtime remains the only writer of Skill files. Verify the daemon is running:

clawdi daemon status

If the user opted out during setup, install it now:

clawdi daemon install

The install command writes a launchd unit on macOS or a systemd --user service on Linux, then loads it. The daemon stays alive across reboots and respawns on crash. Ongoing logs:

• macOS: tail -f ~/.clawdi/serve/logs/daemon.stderr.log
• Linux: journalctl --user -u clawdi-serve.service -f

The control RPC listens on loopback HTTP by default; every RPC request requires the generated bearer token:

clawdi daemon run
clawdi daemon ping

For non-loopback HTTP RPC, use a private network, SSH tunnel, or TLS proxy and pass the generated daemon token through --token on daemon commands or CLAWDI_DAEMON_RPC_TOKEN; treat it as an admin token.

What the user gets:

• Edit a SKILL.md locally → uploaded to the cloud within ~1s
• Agent Skills appear as read-only filesystem projections in the dashboard
• Cloud events never write or delete the Agent's local Skill files
• Daemon offline status visible in the dashboard's agent detail page

Skip this step only if the user explicitly says they want manual sync. clawdi push remains a manual projection fallback; clawdi pull --modules skills requires an explicit Cloud-owned workspace/personal --project and acts as an intentional local import.

If install fails (no launchd / systemd, e.g. inside a minimal container), fall back to running the daemon in the foreground and ask the user to wire their own supervisor:

clawdi daemon run

Sync skills (optional one-time backup)

If the user has authored custom skills under ~/.claude/skills/, ~/.codex/skills/, etc., back them up to the cloud:

clawdi push --modules skills --all-agents

Most users have zero or a handful of authored skills — no preview needed (unlike sessions, skills are deliberately created and don't have privacy concerns). The bundled clawdi skill that clawdi setup installs is automatically excluded. Re-running this is a no-op for unchanged skills.

To intentionally import Skills from a Cloud-owned workspace/personal Project, name that Project explicitly:

clawdi pull --modules skills --project <project> --agent <agent-type>

Agent Project rows are read-only projections, not a restore source, and are rejected by this command. The explicit import commits guarded local bytes; normal Agent sync then projects them to the target Agent Project.

If the user has zero authored skills, push is a no-op. Do not run a Skill import unless the user selected a Cloud-owned source Project.

Extract memories from sessions (optional)

Seed the user's Memory module by extracting facts, preferences, and decisions from the sessions they just pushed. The cloud's configured LLM does the extraction — the agent loops over recent sessions and calls the per-session endpoint via the CLI.

If the user opted out of session upload above, skip this step entirely (there's nothing in the cloud to extract from).

List recent sessions

clawdi session list --all-agents --limit 5 --json

Parse the JSON. Take the id of each session (these are the local session ids — the same key the upload endpoint uses).

If the JSON is empty ([]), tell the user "No recent sessions to extract from — skipping memory bootstrap." and continue to Verify.

Extract per session

For each session id from the list above, run:

clawdi session extract <id> --json

Each call returns {session_id, memories_created}. Sum memories_created across all 5 calls.

Stop the loop early if the FIRST call exits with code 2 — that means the deployment hasn't configured memory extraction. Tell the user "Memory extraction isn't configured on this deployment — skipping." and continue to Verify.

For other failures (5xx, network), keep going — one bad session shouldn't halt the batch. Note the failure count for the summary.

Report

Tell the user:

✓ Extracted N memories from M sessions{P failed if any}

If extraction was unconfigured, say that instead. Either way, continue to Verify.

Verify

clawdi doctor

Every check should be green. Then point the user at their dashboard:

All set. Open your Clawdi Cloud dashboard — you should see N sessions from this machine across {agents}.

Where N = new + updated + unchanged from the previous step, and {agents} is the list registered in setup.

If they opted out of session upload, just confirm setup checks passed and remind them how to push later.

What the user got

After this their account has:

• Memory — memory_search and memory_create MCP tools for long-term cross-agent recall. Seeded with extractions from the sessions just pushed (if memory extraction was configured).
• Connectors — Gmail, GitHub, Notion, etc. They enable services in the dashboard; tools appear automatically in any registered agent.
• Session sync — pushed today; future sessions sync via clawdi push.
• Skill sync — Agent filesystem Skills projected read-only to Cloud; explicit workspace/personal Project imports remain user-directed.
• Vault — encrypted secrets injected into commands via clawdi run.

Troubleshooting

Push reports "0 sessions" but the user has history. The local hash cache may have drifted from the cloud (e.g. after a server-side data restore). Reset it and re-push:

rm -f ~/.clawdi/sessions-lock.json
clawdi push --modules sessions --all-agents --all

clawdi auth complete keeps saying "Still waiting for approval". The user hasn't clicked approve yet. Re-running is safe within the 10-minute window. If it expired, restart from clawdi auth login.

Older CLI doesn't recognize --all-agents. Loop manually over the agents that registered in setup: clawdi push --modules sessions --agent claude_code --all, then --agent codex, and so on.

Older CLI doesn't recognize --exclude-project. Tell the user to upgrade (bun add -g clawdi again) or accept the limitation — without it, only positive selection (--project) works.

Older CLI doesn't have clawdi session list. Use clawdi push --modules sessions --all-agents --all --dry-run — it prints scan totals per agent without the per-project breakdown.