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DRIVER Plugin for Claude Code

A methodology for AI-augmented finance and quantitative tool development.

Cognition Mate (认知伙伴) — 互帮互助,因缘合和,互相成就 Mutual help. Interdependent arising. Accomplishing together.


⚠️ Disclaimer

DRIVER is a development methodology, not financial software.

  • This plugin provides a workflow framework for building tools — it does not execute trades, manage portfolios, or provide financial advice
  • Any financial tools you build using DRIVER require your own validation and testing
  • The authors assume no liability for financial decisions made using tools developed with this methodology
  • This is not investment advice — consult qualified financial professionals for investment decisions
  • Sample code and examples are for educational purposes only

By using this plugin, you acknowledge that:

  1. You are responsible for validating any financial calculations in tools you build
  2. You understand the risks of financial software development
  3. You will not hold the authors liable for any financial losses

What is DRIVER?

DRIVER guides you through six stages from concept to completion:

Stage Purpose Iron Law
Define Research what exists No building without 分头研究 first
Represent Plan part by part Don't reinvent what exists
Implement Build and run Show don't tell
Validate Verify it works Evidence before claims
Evolve Package deliverable Self-contained export
Reflect Capture learnings Document what didn't work

The Philosophy

AI is not a tool you command — it's a thinking partner.

  • You bring: vision, domain expertise, judgment
  • AI brings: patterns, research ability, heavy lifting on code
  • Neither creates alone — meaning emerges from interaction

Installation

From GitHub (Recommended)

# In Claude Code
/plugin marketplace add https://github.com/CinderZhang/driver-plugin
/plugin install driver@driver-plugin

Restart Claude Code after installing.

From Local Folder (For Development)

# In Claude Code
/plugin marketplace add /path/to/driver-plugin
/plugin install driver@driver-dev

Quick Start

# Start Claude Code in your project directory
claude

# Initialize a DRIVER project
/driver:init

# Check available commands
/driver:help

# Begin with research and definition
/driver:define

Available Skills

Utility

Skill Purpose
/driver:init Initialize a new DRIVER project
/driver:status Show progress, suggest next step
/driver:help Full reference with Chinese term explanations

DEFINE Stage

Skill Purpose
/driver:define Research and define product vision (开题调研)

REPRESENT Stage

Skill Purpose
/driver:represent-roadmap Break into 3-5 buildable sections
/driver:represent-datamodel Define core entities
/driver:represent-tokens Choose colors and typography
/driver:represent-shell Design navigation shell
/driver:represent-section Spec a section

IMPLEMENT Stage

Skill Purpose
/driver:implement-data Create sample data
/driver:implement-screen Build and run code

VALIDATE Stage

Skill Purpose
/driver:validate Capture screenshots as evidence

EVOLVE Stage

Skill Purpose
/driver:evolve Generate final export package

REFLECT Stage

Skill Purpose
/driver:reflect Capture learnings and tech stack lessons

For Quant/Finance Work

DRIVER recommends Python + Streamlit over TypeScript/React for analytical tools:

UI:           Streamlit (or Dash/Panel)
Backend:      FastAPI + Pydantic
Calculations: NumPy, Pandas, SciPy
Finance:      numpy-financial, QuantLib
Data:         financialdatasets.ai, Bloomberg, Refinitiv (recommended)
              yfinance, FRED (free alternatives - use at own risk)

Why Python?

  • NumPy handles edge cases (safe division, vectorized ops)
  • Pydantic validates inputs at boundaries
  • No npm complexity, no TypeScript type juggling
  • Better finance libraries

Example Projects

Project Type Key Libraries Data Source Reference
DCF Valuation numpy-financial financialdatasets.ai Damodaran
Portfolio Optimization PyPortfolioOpt, cvxpy Professional data feed Markowitz
Factor Research alphalens, statsmodels WRDS, CRSP Open Source Asset Pricing
Risk Analytics scipy.stats, VaR/CVaR Professional data feed RiskMetrics
Data Pipeline pandas, great_expectations Multiple sources ETL patterns

Data Sources: For reliable results, use professional data providers (financialdatasets.ai, Bloomberg, Refinitiv, FactSet). Free sources like yfinance may have gaps, delays, or inaccuracies.


Key Chinese Terms

Term Pinyin Meaning
认知伙伴 rèn zhī huǒ bàn Cognition Mate — thinking partner
互帮互助 hù bāng hù zhù Mutual help
因缘合和 yīn yuán hé hé Interdependent arising
互相成就 hù xiāng chéng jiù Accomplishing together
开题调研 kāi tí diào yán Open the topic + research (DEFINE)
分头研究 fēn tóu yán jiū Parallel research

License

MIT License — See LICENSE file.


Contributing

Issues and pull requests welcome. Please read the philosophy section first — contributions should align with the Cognition Mate approach.


Author

Cinder Zhang (cinderzhang@gmail.com)


DRIVER was developed through the practice it teaches — human vision and AI collaboration, accomplishing together.

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