Korben00
no-gdid
no-gdid is a PowerShell-based tool to audit and block the Windows Global Device Identifier (GDID), a per-account device ID used by Microsoft and shared with law enforcement, based on verified reverse engineering.
fluencer-predict-track
A set of AI agent skills/rules for Codex, Claude Code, and Cursor that audits investment predictions from public Chinese social media (Zhihu) by verifying them with authoritative data and producing a Markdown report with backtesting and qualitative analysis.
Stars
32
7-day growth
No data
Forks
11
Open issues
0
License
MIT
Last updated
2026-06-29
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It systematically quantifies the accuracy of finfluencer predictions using public sources (central banks, exchanges, FRED, etc.) and includes a backtesting engine that simulates portfolio returns, Sharpe ratio, and position management, making prediction validation rigorous and transparent.
Who it is for
- Investment researchers and analysts
- Finance content consumers who want to fact-check pundits
- Quantitative developers building forecast‑audit tools
- AI assistants users interested in structured reasoning skills
Use cases
- Verify the accuracy of investment predictions made by well‑known Zhihu authors
- Generate a comprehensive 'compilation' report with prediction‑level verdicts and statistical summaries
- Backtest tradable predictions into a simulated portfolio to estimate annualised return and Sharpe ratio
- Compare the performance of multiple finfluencers across different time spans
Strengths
- Supports three major AI agent entry points (Codex, Claude Code, Cursor) from a single repository
- Requires at least 20 prediction samples per target and checks last‑edit timestamps to avoid hindsight bias
- Validates predictions against authoritative public data sources (central banks, stock exchanges, Yahoo Finance, etc.)
- Integrates a backtesting module that outputs net‑asset‑value curves, annualised returns, and Sharpe ratios with clear disclaimers about position sizing
Considerations
- Requires a local Chrome/Chromium instance with CDP enabled, adding setup overhead
- Scraping is primarily designed for Zhihu; extending to other platforms would need modification
- Backtesting assumes a fixed risk‑free rate (2.8%) and default initial capital (1,000,000), with position rules that may affect comparability
README quick start
安装
Description
投资大V合订本：追踪投资大V历史预测，并用公开数据验证准确性
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