A sophisticated decision forecasting engine that utilizes Menos architecture and swarm intelligence to simulate outcomes in a digital sandbox.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install scenique-prevision
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 scenique-prevision 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 Scenique Prevision?
Scenique Prevision is a robust decision forecasting engine integrated into the Openclaw Skills framework. It implements the Prevision layer of the Menos architecture, allowing developers to simulate multi-agent swarms in a digital sandbox before committing to real-world actions. This skill ensures that any decision made within the Openclaw Skills environment is backed by probabilistic modeling and adversarial debate, bridging the gap between raw data and actionable strategy.
Scenique Prevision Use Cases
- Forecasting market movements or asset trading strategies based on historical data.
- Testing project feasibility through multi-perspective agent debates.
- Strategic planning for long-term goals using contextual knowledge from memory layers.
- Risk assessment for complex operational changes in a simulated environment.
How Scenique Prevision Works
- The user initiates a query via the prevision_simulate tool with specific parameters.
- The engine retrieves essential context from the L1 Physical Ledger and L2 Long-term Memory layers.
- The system instantiates a dynamic swarm including Skeptic, Optimist, and Strategist agents to debate the query.
- These agents engage in a simulated interaction within a digital sandbox to explore all possible paths.
- The Path Collapse process synthesizes the simulation into a final probabilistic report on potential outcomes.
Scenique Prevision Setup
To deploy this skill within your Openclaw Skills ecosystem, ensure your gateway has subagent capabilities enabled.
# Enable subagent support in your Openclaw gateway configuration
openclaw config set subagents true
# Install the Scenique Prevision skill
openclaw install scenique-prevision
Scenique Prevision Data Schema & Taxonomy
Scenique Prevision organizes its operations around the Menos data architecture to ensure accuracy:
| Data Component | Description |
|---|---|
| L1 (Physical Ledger) | Provides the immediate environment state and real-time data context. |
| L2 (Long-term Memory) | Sources historical context, past results, and persistent knowledge patterns. |
| Path Collapse Report | A structured output containing probability distributions and agent debate transcripts. |
Scenique Prevision Advanced Features
- Integrated swarm intelligence for diverse perspective modeling during simulations.
- Seamless Menos L1 and L2 architectural hooks for deep contextual awareness.
- Probabilistic path collapse algorithms for simplified decision-making reports.
- Native support for subagent orchestration optimized for Openclaw Skills workflows.
SKILL.md
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