A comprehensive planning engine for live commerce sessions that generates operator-ready show briefs, host scripts, and moderation strategies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install live-commerce-showrunner
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install live-commerce-showrunner using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Live Commerce Showrunner?
Live Commerce Showrunner is a specialized skill designed to bridge the gap between a raw product idea and a professionally executed live selling event. It serves as a digital producer for brands and marketplace teams operating on platforms like TikTok Shop, Douyin, Amazon Live, and Taobao Live. By synthesizing channel context and commercial constraints, it provides a structured framework for high-stakes ecommerce broadcasts.
As part of the Openclaw Skills ecosystem, this tool focuses on the heuristic and strategic side of live commerce. It helps teams define their offer ladder, urgency mechanics, and team responsibilities, ensuring that every minute of the broadcast is optimized for engagement and conversion without requiring direct integration into sensitive live platform data.
Live Commerce Showrunner Use Cases
- Creating a detailed 45-60 minute run of show for new product launches or clearance events.
- Briefing a multi-person crew including hosts, moderators, and operations leads on their specific roles.
- Designing comment-to-conversion plays and urgency hooks to drive immediate GMV during a session.
- Developing contingency plans and risk controls for technical failures or low-traffic scenarios.
- Generating post-live debrief templates to capture learnings and improve future broadcast performance.
How Live Commerce Showrunner Works
- Context Intake: The skill captures critical show data including the target channel, primary goals, product priorities, and pricing constraints.
- Strategy Selection: It identifies the most effective show archetype, such as an education-led session, a high-energy promo, or a guest-hosted launch.
- Sequential Planning: A structured run of show is generated, covering opening hooks, social proof moments, offer stacking, and closing calls-to-action.
- Role Assignment: Specific task lists are created for the host (scripting), moderator (engagement), and ops lead (inventory/logistics).
- Brief Delivery: The system outputs a comprehensive Markdown brief featuring risk controls and a performance debrief checklist.
Live Commerce Showrunner Setup
To integrate this capability into your workflow, ensure your environment is configured for Openclaw Skills and trigger the agent with a specific commerce prompt.
# Example command to initialize the live commerce planning workflow
openclaw run live-commerce-showrunner --prompt "Plan a 60-minute TikTok Shop launch for organic tea"
No API keys for commerce platforms are required, as this skill operates on a heuristic planning model rather than live data access.
Live Commerce Showrunner Data Schema & Taxonomy
The skill organizes planning data into a standardized taxonomy to ensure consistency across different shows and channels:
| Data Component | Description |
|---|---|
| Strategy Summary | High-level objectives, target audience, and channel-specific nuances. |
| Run of Show | Time-blocked segments including hooks, demos, and closing sequences. |
| Offer Ladder | Mapping of coupons, bundles, and limited-time pricing tiers. |
| Team Matrix | Checklists and responsibilities for Host, Moderator, and Ops. |
| Risk & Contingency | Pre-defined responses for low stock, low traffic, or tech issues. |
| Debrief Template | Structured questions to evaluate success metrics post-stream. |
Live Commerce Showrunner Advanced Features
- Multi-Platform Adaptation: Tailors the script and strategy specifically for different platform algorithms (e.g., Douyin's interest-based feed vs. Amazon's search-based shoppers).
- Offer Stacking Logic: Automatically structures complex promotional mechanics like countdown deals and bundle ladders for maximum urgency.
- Failure Mode Modeling: Includes advanced 'what-if' scenarios to help operators pivot strategies in real-time based on viewer behavior.
- Structured Debriefing: Generates a data-ready checklist that helps Openclaw Skills users track improvement over multiple sessions.
SKILL.md
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