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alirezarezvani

Scenario War Room

by Alireza Rezvani · GitHub ↗ · v2.1.1 · MIT-0
cross-platform ✓ Security Clean
361
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0
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2
Active Installs
2
Versions
Install in OpenClaw
/install scenario-war-room
Description
Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all...
Usage Guidance
This package appears coherent and focused on scenario modeling. Before running: (1) open and read scripts/scenario_modeler.py to confirm it matches the visible logic (no subprocess, socket, requests, os.environ access you didn't expect), (2) run it in a guarded environment (virtualenv or sandbox) if you have any doubt, and (3) remember the tool prints analyses and recommended actions but does not itself take actions on your systems or call external services — you remain in control of applying any hedges or operational steps it suggests.
Capability Analysis
Type: OpenClaw Skill Name: scenario-war-room Version: 2.1.1 The 'scenario-war-room' skill bundle is a legitimate tool for business risk modeling and strategic planning. The Python script `scenario_modeler.py` uses only standard libraries to perform mathematical calculations for financial impact and runway analysis, while `SKILL.md` provides clear, non-malicious instructions for the AI agent to facilitate war-room exercises. No evidence of data exfiltration, unauthorized execution, or prompt injection was found.
Capability Assessment
Purpose & Capability
Name/description match the artifacts: SKILL.md describes multi-variable cascade modeling and the package includes a Python scenario_modeler.py that implements that functionality. No unrelated credentials, binaries, or platform hooks are declared.
Instruction Scope
Runtime instructions simply tell the agent/user to run the included Python script or call the provided war-room prompts. The SKILL.md gives facilitation guidance (triggers, hedges) but does not instruct the agent to read system files, environment variables, or call external endpoints. Recommendation: inspect the script before running to confirm there are no hidden network calls (the visible code uses only stdlib and prints output).
Install Mechanism
No install spec is provided (instruction-only style) and the included script is pure Python using only the standard library. No downloads, archives, or third-party package installations are requested.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The SKILL.md and script do not reference secrets or external service tokens.
Persistence & Privilege
Skill is not marked always:true and does not request persistent agent-level privileges. Nothing in the files indicates attempts to modify other skills or system-wide agent settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install scenario-war-room
  3. After installation, invoke the skill by name or use /scenario-war-room
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.1
v2.1.1: optimization, reference splits
v1.0.0
Initial release.
Metadata
Slug scenario-war-room
Version 2.1.1
License MIT-0
All-time Installs 2
Active Installs 2
Total Versions 2
Frequently Asked Questions

What is Scenario War Room?

Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all... It is an AI Agent Skill for Claude Code / OpenClaw, with 361 downloads so far.

How do I install Scenario War Room?

Run "/install scenario-war-room" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Scenario War Room free?

Yes, Scenario War Room is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Scenario War Room support?

Scenario War Room is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Scenario War Room?

It is built and maintained by Alireza Rezvani (@alirezarezvani); the current version is v2.1.1.

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