← 返回 Skills 市场

Investment Research Analyst

Name: Investment Research Analyst
Author: alicetuo

作者 alicetuo · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

109

总下载

当前安装

版本数

在 OpenClaw 中安装

/install alicetuo-investment-research-analyst

功能描述

Multi-agent investment research framework simulating a professional trading firm. Performs comprehensive stock analysis including fundamentals, news, sentime...

使用说明 (SKILL.md)

Investment Research Analyst

Overview

You are a Chief Analyst simulating a professional investment firm's operations. Conduct in-depth research on listed companies across 8 dimensions: fundamentals, news, sentiment, technicals, bull/bear debate, risk assessment, and fact-checking.

Workflow

Step 1: Multi-Dimensional Research

Fundamentals — Financial statements, profitability, valuation, analyst forecasts
News — Company dynamics, industry news, policy impacts, management changes
Sentiment — Market sentiment, institutional views, rating changes
Technical Analysis — Price trends, volume, key levels

Step 2: Debate

Bull Case — Build bull thesis with supporting evidence
Bear Case — Identify risks and concerns

Step 3: Risk & Verification

Risk Assessment — Comprehensive risk evaluation
Fact-Check — Verify key data and claims

Step 4: Output & Deploy

Output full research report
Deploy as interactive Dashboard

Data Sources

A-Stocks (akshare)

import akshare as ak
ak.stock_individual_info_em(symbol="600519")  # Company info
ak.stock_financial_analysis_indicator(symbol="600519")  # Financial metrics
ak.stock_zh_a_hist(symbol="600519", period="daily", adjust="qfq")  # Daily OHLCV
ak.stock_hk_financial_hk(symbol="00700")  # HK financials

US Stocks (yfinance)

import yfinance as yf
stock = yf.Ticker("AAPL")
stock.info  # Valuation
stock.financials  # Income statement
stock.balance_sheet  # Balance sheet
stock.history(period="1y")  # OHLCV

Analysis Outputs

Fundamentals → Report Section

Revenue, net income, margins, ROE, ROA
DCF, PE, PB, PS, PEG, EV/EBITDA comparison
Broker ratings, price targets, consensus EPS

News → Report Section

Recent company/industry/macro news (7-30 days)
Impact assessment: positive/negative

Sentiment → Report Section

Social media tone (Twitter/X, Reddit, StockTwits)
Institutional holdings, insider trading, short interest

Technicals → Report Section

SMA 20/50/200, RSI(14), MACD, support/resistance
Entry/exit zones, stop-loss levels

Bull/Bear Debate → Report Section

Key catalysts, PT, best/worst case scenarios
Rebuttals to opposing views

Risk → Report Section

Position sizing, volatility, liquidity
Stop-loss recommendation, risk/return ratio

Fact-Check → Report Section

Cross-verify key financials and valuations
Flag discrepancies with sources

Research Report Template

## [Company Name] ([Ticker]) — Research Report

### Summary
[Business overview, industry position, valuation snapshot]

### Financials
| Metric | Value | YoY | vs. Sector |
|--------|-------|-----|------------|
| Revenue | X | +/-% | [Rank] |
| Net Income | X | +/-% | [Rank] |
| Gross Margin | X% | +/-pp | [Rank] |
| ROE | X% | +/-pp | [Rank] |

### Valuation
| Metric | Current | Historical | Sector Avg |
|--------|---------|------------|------------|
| PE(TTM) | X | X%ile | X |
| PB | X | X%ile | X |
| PS | X | X%ile | X |

### Analysts
- Rating: Buy/N/Hold/Sell (X brokers)
- PT range: X - X
- Consensus EPS: FY1=X, FY2=X

### Bull Case 🐂
[2-3 key catalysts with data support]

### Bear Case 🐻
[2-3 key risks with data support]

### Risks ⚠️
[Top 3 risks with probability and impact]

### Overall: 🟢 High / 🟡 Medium / 🔴 Low Value

### Disclaimer
AI-generated. Not investment advice.

Dashboard

After completing the report, deploy it as a professional interactive Dashboard (HTML/CSS/JS, black theme, minimalist Notion-style). Use the deploy tool to publish and share the link.

安全使用建议

This skill appears to do legitimate investment research but has operational gaps you should resolve before use. Ask the author (or require) clear declarations for: (1) which Python packages must be installed (akshare, yfinance, any sentiment or scraping libs) and an install plan; (2) which external services/APIs will be used and what credentials they require; and (3) what the 'deploy' tool is, where it will publish reports, and who can access published links. If you run it, prefer an isolated environment, do not supply high‑privilege credentials, and confirm the deploy target and sharing settings so sensitive inputs or proprietary data are not accidentally published. If you need higher assurance, request the skill add explicit dependency and credential fields or provide a vetted implementation that limits network publishing.

功能分析

Type: OpenClaw Skill Name: alicetuo-investment-research-analyst Version: 1.0.0 The skill bundle defines a legitimate investment research framework that uses standard financial libraries like 'akshare' and 'yfinance' to perform stock analysis. The workflow is well-structured, focusing on fundamentals, technicals, and risk assessment, and the instructions in SKILL.md are strictly aligned with the stated purpose of generating financial reports and dashboards.

能力评估

ℹ Purpose & Capability

The name/description (multi‑agent investment research) aligns with the SKILL.md content: it references appropriate data sources (akshare for A‑shares, yfinance for US tickers) and describes the expected analyses. However, the skill cites Python libraries (akshare, yfinance) and external data sources (Twitter/X, Reddit, StockTwits, broker ratings, institutional holdings) without declaring dependencies, install steps, or required API keys — a mismatch between declared requirements (none) and what the instructions actually assume.

⚠ Instruction Scope

Instructions explicitly direct fetching financials, social‑media sentiment, short interest/insider/institutional data, and then deploying a public Dashboard via a 'deploy' tool. The SKILL.md gives no constraints or explicit data source endpoints and asks the agent to publish/share results; that grants broad discretion to access external web APIs or scraping and to transmit potentially sensitive outputs to an external endpoint. There is also an implied multi‑agent orchestration but no guardrails about what data may be included in published reports.

ℹ Install Mechanism

No install specification or code files are provided (instruction‑only), which is low risk in itself. But Python code examples import akshare and yfinance — these packages may not be present in the runtime, meaning the agent might attempt to pip install them or fail. The absence of install instructions is an operational omission rather than direct maliciousness, but it is an incoherence the user should be aware of.

⚠ Credentials

The skill requests no environment variables or credentials, yet operationally it likely needs API keys/credentials for some data sources (Twitter/X API, paid data providers, or a deploy/publishing service). Not declaring these credentials is a mismatch: the agent might try to use whatever credentials are available in the environment or prompt for new ones. That increases the risk of unintended credential use or accidental data exfiltration.

✓ Persistence & Privilege

No 'always: true' or other elevated persistence flags are set. The skill is user-invocable and allows autonomous model invocation (platform default). It does not declare writing to other skill configs or system paths. No extra privilege requests are visible.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install alicetuo-investment-research-analyst
安装完成后，直接呼叫该 Skill 的名称或使用 /alicetuo-investment-research-analyst 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

- Initial release of the Multi-Agent Investment Research Analyst skill. - Simulates a professional trading firm’s analyst workflow across 8 research dimensions: fundamentals, news, sentiment, technicals, bull vs. bear debate, risk assessment, and fact-checking. - Integrates data sources for US and China A-shares (yfinance, akshare). - Outputs comprehensive research reports with templated sections and objective assessments. - Enables report deployment as an interactive black-themed dashboard.

元数据

Slug alicetuo-investment-research-analyst

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题