A comprehensive 3-stage investment analysis system for evaluating stocks across global markets using cold logic, multi-agent debates, and deep AI industry chain mapping.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install investment-framework-bundle
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install investment-framework-bundle using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Investment Framework Bundle is a professional-grade research workflow designed for sophisticated AI agents. It guides users through a rigorous three-stage analysis process: V1 (Logic Decoupling), V2 (Bull/Bear Debate), and V3 (Deep AI Industry Chain Analysis). By utilizing Openclaw Skills, investors can transition from emotional trading to a structured, data-driven approach that encompasses everything from survival rules to quantitative screening. This skill supports A, H, and US markets, providing a Wall Street-level pipeline for analyzing semiconductor, software, and infrastructure investments.
The framework is built to be objective and unforgiving, prioritizing capital preservation through strict risk-control protocols. Whether you are assessing a single stock or mapping an entire sector, this tool ensures that every investment thesis is stress-tested against opposing viewpoints and historical valuation benchmarks.
To utilize this investment system within Openclaw Skills, you must provide the ticker or name of a financial instrument. Use the following triggers to initialize the specific stage of the workflow:
# Initialize stage V1 analysis
"Help me analyze [Ticker] using the investment framework."
# Trigger a stage V2 Bull/Bear debate
"Run a V2 debate for [Ticker]."
# Execute a V3 deep dive for AI stocks
"Perform a V3 AI industry chain deep research on [Ticker]."
The skill organizes its analysis into a structured metadata taxonomy for high clarity and actionable output:
| Module | Key Data Points |
|---|---|
| A-X Framework | Market conditions, Opponent behavior, Error mechanisms, Price deviation, Entry signals, Position sizing, Profit targets, Time limits, Stop-loss events |
| AI Industry Layers | 1. Compute (GPU/HBM), 2. Infrastructure (Data Centers/Power), 3. Cloud Services, 4. Application Layer, 5. Valuation Methodology |
| Debate Dimensions | Fundamentals (Revenue/Cash Flow), Sentiment (Analyst ratings), Macro (Policy/Industry trends), Technicals (MACD/RSI/Support) |
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