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Oraclaw Simulate
by
Whatsonyourmind
· GitHub ↗
· v1.0.0
· MIT-0
140
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1
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Install in OpenClaw
/install oraclaw-simulate
Description
Monte Carlo simulation for AI agents. Run thousands of probabilistic scenarios to model risk, forecast revenue, estimate project timelines, and quantify unce...
Usage Guidance
This skill is coherent with its stated purpose, but it will call an external service using the ORACLAW_API_KEY. Before installing: (1) confirm the API key is for a dedicated account or has minimal privileges (don’t reuse your master keys); (2) understand billing — the SKILL.md lists per-simulation pricing and a USDC payment rail; (3) verify what data is sent to the service (avoid sending sensitive customer or secret data into simulations until you confirm retention/ privacy policies); (4) consider testing with non-sensitive inputs and a limited quota; and (5) if you need to audit network endpoints, ask the vendor for the exact API host/URLs and a privacy/data-retention statement.
Capability Analysis
Type: OpenClaw Skill
Name: oraclaw-simulate
Version: 1.0.0
The skill bundle contains metadata and instructions for a Monte Carlo simulation tool (oraclaw-simulate). The documentation in SKILL.md describes standard probabilistic modeling functionality, requires a standard API key (ORACLAW_API_KEY), and lacks any indicators of malicious intent, data exfiltration, or prompt injection attacks.
Capability Assessment
Purpose & Capability
Name/description (Monte Carlo simulation) align with the declared requirement (ORACLAW_API_KEY) and metadata. Requesting a single API key is expected for a hosted simulation service.
Instruction Scope
SKILL.md contains only simulation instructions and example inputs/outputs and does not instruct the agent to read unrelated files or environment variables. It does not show the exact API endpoints or network behavior (the API key is implied), so you should expect the agent to call the external oraclaw service when invoked.
Install Mechanism
No install spec and no code files — lowest-risk instruction-only skill; nothing is downloaded or written to disk by the skill itself.
Credentials
Only a single environment variable (ORACLAW_API_KEY) is required and declared as the primary credential, which is proportional for a hosted API-based simulation service.
Persistence & Privilege
always is false and autonomous model invocation is the platform default. The skill does not request persistent/privileged presence or modify other skills or system settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install oraclaw-simulate - After installation, invoke the skill by name or use
/oraclaw-simulate - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of oraclaw-simulate.
- Monte Carlo simulation tool for AI agents to model risk, revenue, timelines, and uncertainty.
- Supports six distribution types: normal, lognormal, uniform, triangular, beta, exponential.
- Provides scenario results including mean, standard deviation, percentiles, and histograms.
- API access requires ORACLAW_API_KEY; pricing starts at $0.05 per simulation (1K iterations).
Metadata
Frequently Asked Questions
What is Oraclaw Simulate?
Monte Carlo simulation for AI agents. Run thousands of probabilistic scenarios to model risk, forecast revenue, estimate project timelines, and quantify unce... It is an AI Agent Skill for Claude Code / OpenClaw, with 140 downloads so far.
How do I install Oraclaw Simulate?
Run "/install oraclaw-simulate" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Oraclaw Simulate free?
Yes, Oraclaw Simulate is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Oraclaw Simulate support?
Oraclaw Simulate is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Oraclaw Simulate?
It is built and maintained by Whatsonyourmind (@whatsonyourmind); the current version is v1.0.0.
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