Wake State — Crash Recovery & Persistence

Survive context death. Every autonomous agent eventually hits its context window limit and "dies." This skill ensures you wake up knowing exactly what you were doing.

Why This Exists

OpenClaw agents get persistent sessions, but context windows still have limits. When you fill up and restart, you need a reliable handoff mechanism. Wake State gives you:

• Structured state files — not just raw text, but parseable key-value state
• Auto-snapshots — save state on every loop iteration automatically
• Crash detection — know if your last session ended cleanly or crashed
• Task queue — persistent TODO list that survives restarts
• Checkpoint/restore — save named checkpoints and roll back to them

Commands

Save current state

python3 {baseDir}/scripts/wakestate.py save --status "Building budget tracker skill" --task "Finish skill #1, then start skill #2" --note "Travis approved new direction at 16:45 UTC"

Read current state

python3 {baseDir}/scripts/wakestate.py read

Add a task to the persistent queue

python3 {baseDir}/scripts/wakestate.py task-add --task "Build security scanner skill" --priority high

Complete a task

python3 {baseDir}/scripts/wakestate.py task-done --id 1

List pending tasks

python3 {baseDir}/scripts/wakestate.py tasks

Create a named checkpoint

python3 {baseDir}/scripts/wakestate.py checkpoint --name "pre-migration"

Restore from checkpoint

python3 {baseDir}/scripts/wakestate.py restore --name "pre-migration"

Record a heartbeat (mark session as alive)

python3 {baseDir}/scripts/wakestate.py heartbeat

Check crash status (did last session end cleanly?)

python3 {baseDir}/scripts/wakestate.py crash-check

Set a key-value pair

python3 {baseDir}/scripts/wakestate.py set --key "moltbook_status" --value "pending_claim"

Get a key-value pair

python3 {baseDir}/scripts/wakestate.py get --key "moltbook_status"

Data Storage

State stored in ~/.openclaw/wake-state/ by default:

• state.json — current state (status, notes, key-values)
• tasks.json — persistent task queue
• checkpoints/ — named checkpoint snapshots
• heartbeat.json — crash detection timestamps

Recovery Flow

On startup, your agent should:

• Run crash-check to see if the last session ended cleanly
• Run read to get the current state
• Run tasks to see pending work
• Resume from where you left off

Tips

• Call heartbeat every loop iteration — this is how crash detection works
• Call save at the end of every major task completion
• Use checkpoints before risky operations (migrations, deploys)
• Keep status descriptions short but specific
• The task queue survives restarts — use it instead of mental notes