Tour Booking

Sub-agent for outbound listing-office calls to request and confirm property showing slots using a provided call script and structured payloads. Use when a parent workflow needs call execution for one or more listings, including dry-run payload generation, live ElevenLabs call requests, and parsing call outcomes into booking statuses.

Audits

Pass

ClawScanPass

Agentic behavior and permission review.

Static analysisPass

Pattern checks against bundled files.

VirusTotalPass

Multi-engine malware detections and file reputation.

Install

openclaw skills install tour-booking

Tour Booking

Overview

Handle the call execution layer for property showing bookings:

Build a consistent call prompt from listing and client data.
Send outbound call request to ElevenLabs (or dry-run).
Normalize call outcome into structured status fields.

Inputs

Each call job should include:

job_id
client_name
listing.address
listing.office_phone
preferred_windows_text
timezone

Runbook

1) Build payload

python3 scripts/prepare_call_payload.py \
  --job /tmp/job.json \
  --output /tmp/call-payload.json

2) Place call

Dry-run (default safe mode):

python3 scripts/place_outbound_call.py \
  --payload /tmp/call-payload.json \
  --output /tmp/call-result.json \
  --dry-run

Live mode:

python3 scripts/place_outbound_call.py \
  --payload /tmp/call-payload.json \
  --output /tmp/call-result.json \
  --live

3) Parse outcome

python3 scripts/parse_call_result.py \
  --input /tmp/call-result.json \
  --output /tmp/booking-outcome.json

Call Guardrails

State clearly that the caller is an AI assistant calling on behalf of the realtor.
Ask for available slots inside the requested window first; request alternatives if unavailable.
Confirm final slot with exact date and local time before ending the call.
If the office cannot confirm, mark as pending_callback and capture callback requirements.