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BytesAgain β€Ί Skills β€Ί Plusefin Analysis
πŸ¦€ ClawHub

Plusefin Analysis

by @wanghsinche

AI-ready stock analysis with financial data, options, sentiment, and structured research framework

Versionv1.0.9
Downloads956
Installs1
Stars⭐ 2
#research#finance#legal
TERMINAL
clawhub install plusefin-analysis

πŸ“– About This Skill

name: plusefin-analysis description: AI-ready stock analysis with financial data, options, sentiment, and structured research framework metadata: clawdbot: emoji: "πŸ“ˆ" homepage: "https://github.com/plusefin/plusefin-skill" requires: env: ["PLUSEFIN_API_KEY"] primaryEnv: "PLUSEFIN_API_KEY"

PlusE Financial Analysis

AI-ready financial data research skill with structured research methodology.

Setup

export PLUSEFIN_API_KEY=your_api_key

Research Framework

1. Research Setup

  • Define target (ticker) and time range (6mo / 1y / 2y)
  • Set research objective: valuation analysis / technical outlook / event-driven

    • 2. Data Collection

  • Company Fundamentals: ticker - overview, valuation, ratings
  • Market Sentiment: sentiment / sentiment-history
  • Options Data: options / options-analyze (IV, Greeks, OI)
  • Institutional Holdings: holders - major holders changes
  • Financial Statements: statements (income/balance/cash)
  • Earnings & Insider: earnings / insiders
  • Price History: price-history

    • 3. Hypothesis Formation

    Based on data, formulate hypotheses:
  • Direction: Bullish / Bearish / Neutral
  • Drivers: Valuation reversion, earnings growth, event catalyst, sentiment reversal

    • 4. Evidence Validation

  • Use search capabilities to gather research reports, news, announcements
  • Cross-validate multi-source data timeline consistency
  • Seek evidence supporting or refuting hypotheses

    • 5. Valuation Scenarios

  • Bull Case: Valuation assuming upside catalysts materialize
  • Base Case: Valuation based on current market expectations
  • Bear Case: Valuation assuming downside risks materialize

    • 6. Risk Assessment

  • Downside risks
  • Key assumption risks
  • Potential catalysts and triggers

    • 7. Report Output

    Structured output:
  • Core thesis
  • Evidence summary
  • Valuation scenario comparison
  • Risk warnings
  • Actionable recommendations (if applicable)

    • Each key conclusion must include source citations.

    Usage

    # Set API key
export PLUSEFIN_API_KEY=your_api_key
    Run commands
    
python plusefin.py  [args]

    Commands

    | Command | Usage | Description | |---------|-------|-------------| | ticker | python plusefin.py ticker | Company overview, valuation, ratings | | price-history | python plusefin.py price-history [period] | Historical prices (6mo/1y/2y) | | sentiment | python plusefin.py sentiment | Market sentiment (Fear & Greed) | | sentiment-history | python plusefin.py sentiment-history [days] | Historical sentiment | | options | python plusefin.py options [num] | Options chain | | options-analyze | python plusefin.py options-analyze | Options analysis | | holders | python plusefin.py holders | Institutional holdings | | statements | python plusefin.py statements [type] | Financial statements (income/balance/cash) | | earnings | python plusefin.py earnings | Earnings history | | insiders | python plusefin.py insiders | Insider trading | | news | python plusefin.py news | Stock news | | fred | python plusefin.py fred | Macroeconomic data |

    πŸ’‘ Examples

    # Set API key
export PLUSEFIN_API_KEY=your_api_key
    Run commands
    
python plusefin.py  [args]

    βš™οΈ Configuration

    export PLUSEFIN_API_KEY=your_api_key