A high-fidelity marketing strategy prediction engine that uses five specialized AI agents and real-time data to forecast campaign and product launch outcomes.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install vision-simulator
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install vision-simulator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Vision Simulator is an advanced predictive tool designed for marketers and strategists who need to validate ideas before execution. By leveraging the Openclaw Skills framework, it orchestrates a multi-agent simulation that mimics real-world market dynamics. The skill integrates live data—including news, social trends, and competitor movements—to provide a realistic sandbox for testing campaign forecasts and product launch scenarios.
At its core, the tool moves beyond simple text generation by employing specialized personas that analyze a scenario from various angles, such as consumer psychology, viral potential, and industry benchmarking. This results in a comprehensive prediction report that includes success probabilities and actionable risk assessments, making it an essential asset for data-driven decision-making.
To integrate this skill into your workflow, ensure your environment supports multi-agent spawning.
# Install the Openclaw Skills CLI
npm install -g openclaw-cli
# Add the vision-simulator skill to your agent
openclaw add vision-simulator
# Configure your API keys for real-time data fetching (Pro Feature)
openclaw config --set WEB_FETCH_API_KEY=your_key_here
Vision Simulator organizes data through a sequential pipeline that feeds into a final markdown-formatted report. The taxonomy includes:
| Data Layer | Description |
|---|---|
| Input Scenario | User-defined marketing text and campaign goals. |
| Reality Data | Summarized news feeds and trend metrics from web sources. |
| Persona Insights | Qualitative reactions from 30-35 age-range personas and price-sensitive groups. |
| Metric Table | Success probability (%), Purchase Intent (1-10), and Viral Potential (1-10). |
| Actionable Metadata | Ranked priority items and categorized risk factors. |
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