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Oraclaw Risk

Skill Verified Active

Risk assessment engine for AI agents. Value at Risk (VaR), CVaR, stress testing, and multi-factor risk scoring. Monte Carlo powered. Built for trading agents, lending agents, and portfolio managers.

Purpose

To equip AI agents with precise, mathematically sound risk assessment capabilities, enabling them to make data-driven decisions in financial contexts.

Features

  • Value at Risk (VaR) calculation
  • Conditional Value at Risk (CVaR) calculation
  • Monte Carlo simulation for scenario analysis
  • Stress testing of financial assumptions
  • Multi-factor risk scoring
  • Convergence analysis of risk indicators

Use Cases

  • Calculating VaR for portfolios or individual positions
  • Running stress tests on financial models
  • Quantifying worst-case scenarios with confidence intervals
  • Assessing credit risk and default probability

Non-Goals

  • Performing basic arithmetic or probability calculations outside of financial risk contexts
  • Providing financial advice or investment recommendations
  • Replacing core LLM reasoning capabilities

Documentation

  • info:Configuration & parameter referenceThe SKILL.md mentions the `ORACLAW_API_KEY` environment variable, but doesn't explicitly detail precedence order or default values for other configurations.

Installation

npx skills add Whatsonyourmind/oraclaw

Runs the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.

Quality Score

Verified
98 /100
Analyzed about 16 hours ago

Trust Signals

Last commit12 days ago
Stars8
LicenseMIT
Status
View Source

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