Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
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 pa...
skill openclawclawhub Free
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 pa...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/call-script-template.md, references/elevenlabs-env.md, scripts/parse_call_result.py, scripts/place_outbound_call.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.0
Provenance
- Publisher
- danielfoch
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
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.
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs2 Scripts1 Config
- SKILL.md
- references/call-script-template.md
- references/elevenlabs-env.md
- scripts/parse_call_result.py
- scripts/place_outbound_call.py
- agents/openai.yaml