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einstein-research-bubble-dv爱因斯坦研究气泡 dv

Agent Skill

einstein-research-bubble-dv 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

4,113

周安装

168

GitHub Stars

公开资料未说明

下载量

1,331
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:einstein-research-bubble-dv(爱因斯坦研究气泡 dv)
来源仓库:https://github.com/clawdiri-ai/einstein-research-bubble-dv
安装命令:
openclaw skills install einstein-research-bubble-dv
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 einstein-research-bubble-dv

简介

einstein-research-bubble-dv 基于明斯基/金德尔伯格框架评估市场泡沫风险。

  • 专为 OpenClaw 设计,适用于识别潜在资产过热信号。
  • 通过 ClawHub 安装,优先考虑客观指标而非主观子分数。
  • 使用前需确认权限范围、维护状态,以及是否会触发宏观经济数据分析操作。
  • 建议定期运行并结合基本面信息综合研判市场状态。

SKILL.md

id
einstein-research-bubble
name
Einstein Research — Market Bubble Risk Detector
description
Evaluates market bubble risk through quantitative, data-driven analysis using a revised Minsky/Kindleberger framework. Prioritizes objective metrics over subjective impressions to prevent confirmation bias and support practical investment decisions.
version
1.0.0
author
DaVinci
last_amended_at
null
trigger_patterns
[]
pre_conditions
git_repo_required
false
tools_available
[]
expected_output_format
natural_language

Market Bubble Risk Detector

Overview

This skill evaluates market bubble risk through a quantitative, data-driven analysis based on a revised Minsky/Kindleberger framework. It prioritizes objective metrics over subjective impressions to prevent confirmation bias and support practical investment decisions.

Core Principles:

  • Data over Narrative: Relies on measurable data, not just "it feels frothy."
  • Composite Score: Generates a score from 0-100 to quantify bubble risk.
  • Multi-Factor Model: Incorporates sentiment, valuation, leverage, market structure, and new issuance data.
  • Action-Oriented: Provides clear thresholds for tactical adjustments (e.g., raising cash, hedging).

When to Use This Skill

Explicit Triggers:

  • "Are we in a stock market bubble?"
  • "Analyze the risk of a market crash."
  • "Is the market overvalued?"
  • "Should I be taking profits?"
  • User asks about "bubble risk," "market froth," "irrational exuberance," or "Minsky moment."

Implicit Triggers:

  • User expresses anxiety about high valuations or a rapid market run-up.
  • User is considering de-risking their portfolio.

Workflow

Step 1: Execute the Data Collection and Analysis Script

The bubble-detector CLI tool automates the entire process.

bubble-detector run

The script performs the following actions:

  1. Fetches Data: Collects data for each of the 7 quantitative indicators.

- Put/Call Ratio (CBOE) - VIX Index (CBOE) - Margin Debt (FINRA) - Market Breadth (% Stocks > 200d MA) - IPO Issuance (e.g., from a public data source) - Retail Volume as % of Total - Forward P/E Ratio vs. Historical Average

  1. Normalizes Indicators: For each indicator, it calculates a percentile rank over the last 5 years. A rank of 100 means the indicator is at its most "bubbly" level in 5 years.
  2. Calculates Composite Score: A weighted average of the normalized indicator scores.

- Sentiment (Put/Call, VIX, Retail Volume): 40% - Leverage (Margin Debt): 20% - Market Structure (Breadth): 20% - Valuation & Issuance (P/E, IPOs): 20%

  1. Generates Report: Outputs a JSON file and a Markdown summary.

Step 2: Analyze the Report

JSON Output (bubble_report_YYYY-MM-DD.json):

  • Contains the raw data, normalized scores for each indicator, and the final composite score.

Markdown Report (bubble_report_YYYY-MM-DD.md):

  • Overall Bubble Score: e.g., "78 / 100 (High Risk)"
  • Indicator Dashboard: A table showing the current value and normalized score for each of the 7 indicators.
  • Key Drivers: Highlights which indicators are contributing most to the high score.
  • Historical Context: Compares the current score to levels seen before previous market corrections.
  • Recommended Posture: Translates the score into a tactical recommendation.

Interpretation & Recommended Actions

The composite score maps to specific risk postures:

  • 0-40 (Low Risk - "Accumulate"):

- *Characteristics*: Fear is high, valuations are reasonable, leverage is low. - *Action*: A good time to be deploying capital and taking on risk.

  • 41-60 (Moderate Risk - "Cautious Accumulation"):

- *Characteristics*: Market is healthy but not cheap. Some signs of optimism are emerging. - *Action*: Continue to invest, but perhaps with a greater focus on quality.

  • 61-80 (High Risk - "Hold & Hedge"):

- *Characteristics*: Greed is prevalent, valuations are stretched, breadth may be narrowing. - *Action*: Hold existing positions, but stop new aggressive buying. Consider adding hedges (e.g., puts) or raising a small amount of cash.

  • 81-100 (Very High Risk - "Distribute & Protect"):

- *Characteristics*: Euphoria, extreme valuations, high leverage, widespread speculation. - *Action*: Systematically take profits from high-beta positions. Raise significant cash (e.g., 20-40%). Actively hedge the remaining portfolio. This is the time to be selling to the optimists.

Important Considerations

  • Not a Timing Tool: This skill indicates *when risk is high*, not the exact top of the market. Bubbly conditions can persist for months.
  • Context is Key: Always present the score in the context of the underlying indicators. A high score driven by stretched valuations is different from one driven by extreme sentiment.
  • No Panicking: The goal is to make small, rational adjustments to risk exposure, not to sell everything in a panic.

适合场景

01

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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

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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

79.46%
按下载量换算1,058

安全审计

VirusTotal

通过

ClawScan

通过

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。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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