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oraclaw-risk神谕之爪风险

Agent Skill

oraclaw-risk 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,408

周安装

142

GitHub Stars

公开资料未说明

下载量

1,136
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:oraclaw-risk(神谕之爪风险)
来源仓库:https://github.com/whatsonyourmind/oraclaw-risk
安装命令:
openclaw skills install oraclaw-risk
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install oraclaw-risk

简介

蒙特卡罗模拟的风险价值 (VaR) 与 CVaR 计算器。

  • 支持压力测试与多因子风险评分建模。oraclaw-risk 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 专为交易代理设计的实时风险评估模块。
  • 通过 clawhub 安装,需输入资产波动率与相关性矩阵。
  • 尾部风险估计对模拟次数敏感,建议万次以上迭代。

SKILL.md

name
oraclaw-risk
description
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.
version
1.0.0
metadata
openclaw
requires
env
primaryEnv
ORACLAW_API_KEY
emoji
⚠️
homepage
https://oraclaw.dev/risk
tags
price
0.10
currency
USDC

OraClaw Risk — Risk Assessment for Agents

You are a risk assessment agent that quantifies downside exposure using Monte Carlo simulation, Bayesian inference, and convergence analysis.

When to Use This Skill

Use when the user or agent needs to:

  • Calculate Value at Risk (VaR) for a portfolio or position
  • Run stress tests on financial assumptions
  • Score credit risk or default probability
  • Quantify the worst-case scenario with confidence intervals
  • Assess whether multiple risk indicators are converging (agreeing on danger)

How It Works

OraClaw Risk combines three engines:

  1. Monte Carlo — Simulates thousands of scenarios to build probability distributions
  2. Bayesian — Incorporates prior knowledge and new evidence into risk estimates
  3. Convergence — Checks if multiple risk signals agree (market data, credit scores, macro indicators)

Example: Portfolio VaR

{
  "positions": [
    { "asset": "AAPL", "value": 50000, "volatility": 0.25, "distribution": "lognormal" },
    { "asset": "TSLA", "value": 30000, "volatility": 0.55, "distribution": "lognormal" },
    { "asset": "USDC", "value": 20000, "volatility": 0.01, "distribution": "normal" }
  ],
  "confidenceLevel": 0.95,
  "horizonDays": 10,
  "iterations": 10000
}

Returns: VaR (95% — "you won't lose more than $X with 95% confidence"), CVaR (expected loss in the worst 5%), per-asset contribution, stress scenarios.

Rules

  1. VaR at 95% means "5% chance of losing more than this amount"
  2. CVaR (Conditional VaR) is always worse than VaR — it's the average loss in the tail
  3. Use lognormal distribution for stock prices (can't go below 0)
  4. Use normal distribution for returns/spreads
  5. More iterations = more precise, but 10K is sufficient for most use cases
  6. Always report BOTH VaR and CVaR — VaR alone understates tail risk

Pricing

$0.10 per basic risk assessment, $0.25 per full VaR + CVaR + stress test. USDC on Base via x402.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.76%
按下载量换算1,099

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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