research analyst

AI-powered US/China/HK stock & crypto research with 8-dimension analysis, China market reports (东方财富/新浪/财联社/腾讯/同花顺), portfolio tracking, and trend detection...

Security Scan

The skill's described functionality (local Python scripts for market research) does not match what it asks for: it requires unexplained credentials (AUTH_TOKEN, CT0), instructs running scripts that are not included, and proposes installing global tools (brew uv, npm bird) — these inconsistencies merit caution before installing.

Purpose & Capability

The skill claims to be a local Python-based research tool but requires two environment variables (AUTH_TOKEN, CT0) that are not explained in the README/SKILL.md. AUTH_TOKEN/CT0 look like Twitter/X auth tokens or generic secret names; they are not justified by the stated data sources other than an optional 'bird' (Twitter/X) CLI. Requiring these secrets by default is disproportionate to the core purpose (stock/crypto analysis).

Instruction Scope

SKILL.md instructs the agent to run many scripts under scripts/*.py (uv run {baseDir}/scripts/...), but the published package contains no code files—only SKILL.md, README.md, and an upload note. The runtime instructions therefore reference files that do not exist, which is an incoherence: the skill cannot perform the claimed behavior as published. SKILL.md also references social scraping (Twitter/X) and optional bird CLI use, which implies credentialed web access not gated or explained in the instructions.

Install Mechanism

Install metadata calls for brew installing the 'uv' formula and (in install steps) running 'npm install -g @steipete/bird' to install bird globally. Brew and npm installs are common but modify the host environment and install network-retrieved packages; requiring a global npm install is higher-friction and has systemic impact. There is no packaged code included in the skill itself, so the install steps point to external tool installs rather than installing the skill's own code.

Credentials

The skill lists two required environment variables (AUTH_TOKEN, CT0) with no in-SKILL justification or documentation of what service they target. CT0 is commonly a Twitter/X cookie name; AUTH_TOKEN is generic. Making these required for all users — despite the skill having many non-Twitter data sources — is disproportionate and risks credential exposure if users supply secrets without understanding use.

Persistence & Privilege

The skill is not marked always:true and does not request config paths or claim system-wide privileges. It does ask to install system tools (brew, npm global package), but it does not request persistent platform privileges or modify other skills according to the metadata provided.

What to consider before installing

Do not install or provide secrets yet. Ask the publisher for the missing code (the scripts/ folder) or a link to a reproducible release; verify what AUTH_TOKEN and CT0 specifically are and why they are required (if they're Twitter/X cookies or API tokens, only supply them if you trust the source and prefer using a sandboxed environment). Avoid global npm installs (bird) or brew installs unless you trust the package and understand their scope. Prefer to run this project from a vetted GitHub release or in an isolated VM/container and inspect the actual scripts for any credential usage, network endpoints, or data-exfiltration before supplying secrets.

OpenClaw Research Analyst v1.0

OpenClaw 研究分析师 v1.0

⚠️ Installation Required: This skill requires Python 3.10+, uv package manager, and optional dependencies. See installation instructions below.

📦 Source Code: https://github.com/ZhenRobotics/openclaw-research-analyst

English | 中文

Analyze US stocks, China A-shares, Hong Kong stocks, and cryptocurrencies with 8-dimension analysis, China market multi-source reports (东方财富/新浪/财联社/腾讯/同花顺), portfolio management, watchlists, alerts, dividend analysis, and viral trend detection.

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Core Features

• 📊 8-Dimension Analysis — Comprehensive stock scoring (earnings, fundamentals, analysts, momentum, sentiment, sector, market, history)
• 💰 Dividend Analysis — Yield, payout ratio, 5-year growth, safety score
• 📈 Portfolio Management — Track holdings, P&L, concentration warnings
• ⏰ Watchlist + Alerts — Price targets, stop losses, signal changes
• 🔥 Hot Scanner — Multi-source viral trend detection (CoinGecko, Google News, Twitter/X)
• 🔮 Rumor Detector — Early signals for M&A, insider trades, analyst actions
• 🌏 China Markets — A-share & Hong Kong data (东方财富, 新浪, 财联社, 腾讯, 同花顺)
• 🪙 Crypto Support — Top 20 cryptos with BTC correlation
• ⚡ Fast Mode — Skip slow analyses for quick checks

Quick Commands

Stock Analysis

# Basic analysis
uv run {baseDir}/scripts/stock_analyzer.py AAPL

# Fast mode (skips insider trading & breaking news)
uv run {baseDir}/scripts/stock_analyzer.py AAPL --fast

# Compare multiple
uv run {baseDir}/scripts/stock_analyzer.py AAPL MSFT GOOGL

# Crypto
uv run {baseDir}/scripts/stock_analyzer.py BTC-USD ETH-USD

Dividend Analysis

# Analyze dividends
uv run {baseDir}/scripts/dividend_analyzer.py JNJ

# Compare dividend stocks
uv run {baseDir}/scripts/dividend_analyzer.py JNJ PG KO MCD --output json

Dividend Metrics:

• Dividend Yield & Annual Payout
• Payout Ratio (safe/moderate/high/unsustainable)
• 5-Year Dividend Growth (CAGR)
• Consecutive Years of Increases
• Safety Score (0-100)
• Income Rating (excellent/good/moderate/poor)

Watchlist + Alerts

# Add to watchlist
uv run {baseDir}/scripts/watchlist_manager.py add AAPL

# With price target alert
uv run {baseDir}/scripts/watchlist_manager.py add AAPL --target 200

# With stop loss alert
uv run {baseDir}/scripts/watchlist_manager.py add AAPL --stop 150

# Check for triggered alerts
uv run {baseDir}/scripts/watchlist_manager.py check

Alert Types:

• 🎯 Target Hit — Price >= target
• 🛑 Stop Hit — Price <= stop
• 📊 Signal Change — BUY/HOLD/SELL changed

Portfolio Management

# Create portfolio
uv run {baseDir}/scripts/portfolio_manager.py create "Tech Portfolio"

# Add assets
uv run {baseDir}/scripts/portfolio_manager.py add AAPL --quantity 100 --cost 150

# View portfolio
uv run {baseDir}/scripts/portfolio_manager.py show

🌏 China Market Reports

# Complete China market report (all sources)
python3 {baseDir}/scripts/cn_market_report.py

# Market rankings from 东方财富
python3 {baseDir}/scripts/cn_market_rankings.py

# Stock quotes from 新浪财经
python3 {baseDir}/scripts/cn_stock_quotes.py 600519  # 贵州茅台

# Financial news from 财联社
python3 {baseDir}/scripts/cn_cls_telegraph.py

# Money flow analysis from 腾讯财经
python3 {baseDir}/scripts/cn_tencent_moneyflow.py

# Stock diagnosis from 同花顺
python3 {baseDir}/scripts/cn_ths_diagnosis.py 600519

China Data Sources (5 Major Platforms):

• 📊 东方财富 (East Money) — Market rankings, sector analysis, hot stocks
• 💹 新浪财经 (Sina Finance) — Real-time quotes, A-share & Hong Kong
• 📰 财联社 (CLS) — Breaking financial news, market telegraph
• 💰 腾讯财经 (Tencent Finance) — Money flow analysis, capital tracking
• 🔍 同花顺 (THS) — Stock diagnosis, technical analysis

What You Get:

• A-share (沪深) and Hong Kong stock data
• Market hot lists and sector rotations
• Real-time capital flow tracking
• Breaking financial news and announcements
• Individual stock technical diagnosis

🔥 Hot Scanner

# Full scan - find what's trending NOW
python3 {baseDir}/scripts/trend_scanner.py

# Fast scan (skip social media)
python3 {baseDir}/scripts/trend_scanner.py --no-social

# JSON output for automation
python3 {baseDir}/scripts/trend_scanner.py --json

Data Sources:

• 📊 CoinGecko Trending — Top 15 trending coins
• 📈 CoinGecko Movers — Biggest gainers/losers
• 📰 Google News — Finance & crypto headlines
• 📉 Yahoo Finance — Gainers, losers, most active
• 🐦 Twitter/X — Social sentiment (requires auth)

🔮 Rumor Scanner

# Find early signals, M&A rumors, insider activity
python3 {baseDir}/scripts/rumor_detector.py

What it finds:

• 🏢 M&A Rumors — Merger, acquisition, takeover bids
• 👔 Insider Activity — CEO/Director buying/selling
• 📊 Analyst Actions — Upgrades, downgrades, price target changes
• 🐦 Twitter Whispers — "hearing that...", "sources say...", "rumor"
• ⚖️ SEC Activity — Investigations, filings

Analysis Dimensions

Stocks (8 dimensions)

Dimension	Weight	Description
Earnings Surprise	30%	EPS beat/miss
Fundamentals	20%	P/E, margins, growth
Analyst Sentiment	20%	Ratings, price targets
Historical	10%	Past earnings reactions
Market Context	10%	VIX, SPY/QQQ trends
Sector	15%	Relative strength
Momentum	15%	RSI, 52-week range
Sentiment	10%	Fear/Greed, shorts, insiders

Crypto (3 dimensions)

• Market Cap & Category
• BTC Correlation (30-day)
• Momentum (RSI, range)

Performance Options

Flag	Effect	Speed
(default)	Full analysis	60-120s
--no-insider	Skip SEC EDGAR	50-90s
--fast	Skip insider + news	45-75s

Supported Cryptos (Top 20)

BTC, ETH, BNB, SOL, XRP, ADA, DOGE, AVAX, DOT, MATIC, LINK, ATOM, UNI, LTC, BCH, XLM, ALGO, VET, FIL, NEAR

(Use -USD suffix: BTC-USD, ETH-USD)

Disclaimer

⚠️ NOT FINANCIAL ADVICE. For informational purposes only. Consult a licensed financial advisor before making investment decisions.

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中文版本

⚠️ 需要安装: 本技能需要 Python 3.10+、uv 包管理器和可选依赖。详见下方安装说明。

📦 源代码: https://github.com/ZhenRobotics/openclaw-research-analyst

English | 中文

使用 8 维度分析系统分析美股、A 股、港股和加密货币，提供中国市场多源报告（东方财富/新浪/财联社/腾讯/同花顺）、投资组合管理、监控列表、警报、股息分析和病毒式趋势检测。

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📦 安装与依赖

必需

• Python 3.10+ - 核心运行环境
• uv - Python 包管理器 (brew install uv 或访问 https://github.com/astral-sh/uv)
• Git - 用于克隆仓库

可选

• bird CLI - Twitter/X 集成 (npm install -g @steipete/bird)
• 环境变量 (仅 Twitter/X 功能需要):
  • AUTH_TOKEN - X.com 认证令牌
  • CT0 - X.com CT0 令牌

安装步骤

# 从 GitHub 克隆
git clone https://github.com/ZhenRobotics/openclaw-research-analyst.git
cd openclaw-research-analyst

# 安装 Python 依赖
uv sync

# 验证安装
uv run scripts/stock_analyzer.py --help

安全说明

• ✅ 所有源代码可在 GitHub 查看（已验证）
• ✅ 核心功能无需凭证
• ✅ Twitter/X 凭证仅存储在本地 .env 文件
• ✅ 所有 API 调用使用公开端点（Yahoo Finance、CoinGecko 等）

核心功能

• 📊 8 维度分析 — 综合股票评分（盈利、基本面、分析师、动量、情绪、板块、市场、历史）
• 💰 股息分析 — 收益率、派息比率、5 年增长率、安全评分
• 📈 投资组合管理 — 追踪持仓、盈亏、集中度警告
• ⏰ 监控列表 + 警报 — 目标价、止损、信号变化
• 🔥 热点扫描器 — 多源病毒式趋势检测（CoinGecko、Google News、Twitter/X）
• 🔮 传闻检测器 — M&A、内部交易、分析师行动的早期信号
• 🌏 中国市场 — A 股和港股数据（东方财富、新浪、财联社、腾讯、同花顺）
• 🪙 加密货币支持 — 前 20 大加密货币，含 BTC 相关性
• ⚡ 快速模式 — 跳过慢速分析以快速检查

快速命令

股票分析

# 基础分析
uv run {baseDir}/scripts/stock_analyzer.py AAPL

# 快速模式（跳过内部交易和突发新闻）
uv run {baseDir}/scripts/stock_analyzer.py AAPL --fast

# 比较多个股票
uv run {baseDir}/scripts/stock_analyzer.py AAPL MSFT GOOGL

# 加密货币
uv run {baseDir}/scripts/stock_analyzer.py BTC-USD ETH-USD

股息分析

# 分析股息
uv run {baseDir}/scripts/dividend_analyzer.py JNJ

# 比较股息股票
uv run {baseDir}/scripts/dividend_analyzer.py JNJ PG KO MCD --output json

股息指标：

• 股息率与年度派息
• 派息比率（安全/适中/高/不可持续）
• 5 年股息增长率（CAGR）
• 连续增长年数
• 安全评分（0-100）
• 收益评级（优秀/良好/适中/差）

监控列表 + 警报

# 添加到监控列表
uv run {baseDir}/scripts/watchlist_manager.py add AAPL

# 设置目标价警报
uv run {baseDir}/scripts/watchlist_manager.py add AAPL --target 200

# 设置止损警报
uv run {baseDir}/scripts/watchlist_manager.py add AAPL --stop 150

# 检查触发的警报
uv run {baseDir}/scripts/watchlist_manager.py check

警报类型：

• 🎯 目标价触发 — 价格 >= 目标价
• 🛑 止损触发 — 价格 <= 止损价
• 📊 信号变化 — 买入/持有/卖出信号改变

投资组合管理

# 创建投资组合
uv run {baseDir}/scripts/portfolio_manager.py create "科技投资组合"

# 添加资产
uv run {baseDir}/scripts/portfolio_manager.py add AAPL --quantity 100 --cost 150

# 查看投资组合
uv run {baseDir}/scripts/portfolio_manager.py show

🌏 中国市场报告

# 完整中国市场报告（所有数据源）
python3 {baseDir}/scripts/cn_market_report.py

# 东方财富榜单数据
python3 {baseDir}/scripts/cn_market_rankings.py

# 新浪财经实时行情
python3 {baseDir}/scripts/cn_stock_quotes.py 600519  # 贵州茅台

# 财联社财经快讯
python3 {baseDir}/scripts/cn_cls_telegraph.py

# 腾讯财经资金流向
python3 {baseDir}/scripts/cn_tencent_moneyflow.py

# 同花顺个股诊断
python3 {baseDir}/scripts/cn_ths_diagnosis.py 600519

中国数据来源（5 大平台）：

• 📊 东方财富 — 市场排行榜、板块分析、热门股票
• 💹 新浪财经 — 实时行情、A 股与港股
• 📰 财联社 — 突发财经新闻、市场电报
• 💰 腾讯财经 — 资金流向分析、资金追踪
• 🔍 同花顺 — 个股诊断、技术分析

获取内容：

• A 股（沪深）和港股数据
• 市场热点榜单和板块轮动
• 实时资金流向追踪
• 突发财经新闻和公告
• 个股技术诊断报告

🔥 热点扫描器

# 完整扫描 - 发现当前热门
python3 {baseDir}/scripts/trend_scanner.py

# 快速扫描（跳过社交媒体）
python3 {baseDir}/scripts/trend_scanner.py --no-social

# JSON 输出用于自动化
python3 {baseDir}/scripts/trend_scanner.py --json

数据来源：

• 📊 CoinGecko 热门榜 — 前 15 名热门币种
• 📈 CoinGecko 涨跌榜 — 最大涨幅/跌幅
• 📰 Google News — 财经和加密货币新闻
• 📉 Yahoo Finance — 涨幅榜、跌幅榜、最活跃
• 🐦 Twitter/X — 社交媒体情绪（需要认证）

🔮 传闻扫描器

# 发现早期信号、并购传闻、内部交易
python3 {baseDir}/scripts/rumor_detector.py

发现内容：

• 🏢 并购传闻 — 合并、收购、收购要约
• 👔 内部交易 — CEO/董事买入/卖出
• 📊 分析师行动 — 升级、降级、目标价变化
• 🐦 Twitter 传言 — "据说..."、"有消息称..."、"传闻"
• ⚖️ SEC 活动 — 调查、文件

分析维度

股票（8 个维度）

维度	权重	描述
盈利惊喜	30%	EPS 超预期/低于预期
基本面	20%	市盈率、利润率、增长率
分析师情绪	20%	评级、目标价
历史模式	10%	过往盈利反应
市场背景	10%	VIX、SPY/QQQ 趋势
板块	15%	相对强度
动量	15%	RSI、52 周区间
情绪	10%	恐惧贪婪、空头、内部交易

加密货币（3 个维度）

• 市值与分类
• BTC 相关性（30 天）
• 动量（RSI、区间）

性能选项

参数	效果	速度
(默认)	完整分析	60-120 秒
--no-insider	跳过 SEC EDGAR	50-90 秒
--fast	跳过内部交易 + 新闻	45-75 秒

支持的加密货币（前 20）

BTC, ETH, BNB, SOL, XRP, ADA, DOGE, AVAX, DOT, MATIC, LINK, ATOM, UNI, LTC, BCH, XLM, ALGO, VET, FIL, NEAR

（使用 -USD 后缀：BTC-USD、ETH-USD）

免责声明

⚠️ 非投资建议。 仅供参考。投资前请咨询持牌财务顾问。