help

name	help
description	DRIVER overview, available skills, and philosophy explanation

DRIVER™ Help

What is DRIVER™?

DRIVER™ is a methodology for building finance and quantitative analysis tools with AI assistance. It guides you from concept to completion through six stages.

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The Philosophy: Cognition Mate (认知伙伴)

Core principle: 互帮互助，因缘合和，互相成就

Chinese	Pinyin	Meaning
互帮互助	hu bang hu zhu	Mutual help, helping each other
因缘合和	yin yuan he he	Causes and conditions coming together (interdependent arising)
互相成就	hu xiang cheng jiu	Accomplishing together, mutual achievement

What this means in practice:

• AI is not a tool you command — it's a thinking partner
• You bring vision and domain expertise; AI brings patterns and research
• Neither creates alone — meaning emerges from interaction
• The relationship is collaborative, not transactional

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The Six Stages

DEFINE (开题调研)
    "What are we building? What already exists?"
    开题 = Open the topic  调研 = Research/investigate
                       ↓
REPRESENT
    "How do we break this into buildable pieces?"
    Roadmap, data model, sections
                       ↓
IMPLEMENT
    "Build it, run it, show it"
    Show don't tell — code speaks louder than plans
                       ↓
VALIDATE
    "Cross-check your instruments"
    Known answers, reasonableness, edges, AI blind spots
                       ↓
EVOLVE
    "Package the final deliverable"
    Self-contained export, ready for production
                       ↓
REFLECT (Optional)
    "What did we learn?"
    Capture tech stack lessons, especially failures

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Project Structure

DRIVER uses a flat, easy-to-navigate file structure. All project files live in a single folder (default: my-project/, customizable via .driver.json):

Python (Streamlit) — Recommended for quant/finance:

repo-root/
├── .driver.json                  # Project config
├── [project-name]/               # DRIVER docs and specs
│   ├── README.md                 # You are here
│   ├── research.md               # Created by /research or /define
│   ├── product-overview.md       # Created by /define (your PRD)
│   ├── roadmap.md                # Created by /represent-roadmap
│   ├── spec-[section].md         # Created by /represent-section
│   ├── data-model.md             # Created by /represent-datamodel
│   ├── validation.md             # Created by /validate
│   └── reflect.md                # Created by /reflect
├── app.py                        # Main Streamlit entry point
├── pages/                        # Section pages (auto-discovered by Streamlit)
├── calculations/                 # Core logic (pure Python, testable)
└── data/                         # Data loading and samples

React + TypeScript — For web app UIs:

.driver.json                      # Project config (folder name, project type)
my-project/
├── README.md                     # Project overview and structure
├── research.md                   # Research findings (分头研究)
├── product-overview.md           # Product definition (your PRD)
├── roadmap.md                    # 3-5 buildable sections
├── data-model.md                 # Core entities and relationships
├── validation.md                 # Cross-check results (all sections)
├── reflect.md                    # Learnings and retrospective
├── spec-[section-name].md        # Section specifications
├── design/                       # Web apps only
│   ├── tokens.json               # Colors and typography
│   └── shell.md                  # Navigation shell spec
└── build/                        # Implementation artifacts
    └── [section-id]/
        ├── data.json             # Sample data
        └── types.ts              # TypeScript interfaces

Human-readable documents live at the project root. Implementation artifacts live in build/ (React) or at the repo root (Python).

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Key Concepts

分头研究 (fen tou yan jiu)

"Parallel research" — Before building anything, research what exists. You focus on your unique needs; AI researches existing libraries, papers, implementations.

很可能已经有类似的了 = "There's probably something similar already"

Show Don't Tell

Don't explain what you'll build. Build it. Run it. Let them see it.

The fastest feedback loop: See result → Give feedback → Iterate → See updated result

KISS — Keep It Simple, Structured

• Simple and logical beats elegant and fancy
• Quants need clear data tables, not animations
• A 500-line Python script beats a 50-file TypeScript project

Persistent Artifacts

Every DRIVER stage produces a markdown file — research.md, product-overview.md, roadmap.md, spec files. These are your shared mutable state:

• They survive context window limits (chat history gets compressed; files don't)
• They enable asynchronous review (read at your own pace, catch mistakes)
• They serve as review surfaces where you annotate corrections

Rule: If research, a plan, or a decision lives only in chat, it will get lost. Write it to a file.

The Annotation Cycle

After AI writes a plan or spec, don't just say "looks good." Review it in your editor:

1. AI writes the plan/spec to a markdown file
2. You open it and add inline notes (corrections, domain knowledge, rejected approaches)
3. Send it back: "Update based on my annotations — don't implement yet"
4. AI revises the document
5. Repeat steps 1-4 until the plan is right (typically 1-6 rounds)

This is where the real creative work happens. Implementation should be mechanical.

Mermaid Diagrams

DRIVER uses Mermaid diagrams as standard visual documentation:

• System context — in product-overview.md (how the tool fits in the workflow)
• Dependencies — in roadmap.md (build order between sections)
• User flows — in spec files (step-by-step interaction)
• ER diagrams — in data-model.md (entity relationships)
• Decision landscapes — in research.md (comparing options)

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Available Skills

Skill	Stage	Purpose
/finance-driver:init	Setup	Initialize project structure
/finance-driver:status	Any	Check progress, get suggestions
/finance-driver:help	Any	This help page
/finance-driver:research	Any	Lightweight 分头研究 — research libraries, approaches, references
/finance-driver:define	DEFINE	Research and define vision
/finance-driver:represent-roadmap	REPRESENT	Break into sections
/finance-driver:represent-datamodel	REPRESENT	Define core entities
/finance-driver:represent-tokens	REPRESENT	Colors/typography (web apps)
/finance-driver:represent-shell	REPRESENT	Navigation shell (web apps)
/finance-driver:represent-section	REPRESENT	Spec a section
/finance-driver:implement-data	IMPLEMENT	Sample data (web apps)
/finance-driver:implement-screen	IMPLEMENT	Build and run code
/finance-driver:validate	VALIDATE	Cross-check: known answers, reasonableness, edges, AI risks
/finance-driver:evolve	EVOLVE	Generate export package
/finance-driver:reflect	REFLECT	Capture learnings

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Recommended Stack for Finance/Quant

UI:           Streamlit (or Dash/Panel)
Backend:      FastAPI + Pydantic
Calculations: NumPy, Pandas, SciPy
Finance:      numpy-financial, QuantLib
Data Sources: See README for tiered recommendations
              LLM-Native: financialdatasets.ai, Alpha Vantage, EODHD
              MCP Available: Polygon.io, S&P Global/Kensho
              Free (verify): yfinance, FRED
Storage:      SQLite → PostgreSQL, Parquet files
Testing:      pytest + Hypothesis

Data Quality Matters: For LLM-driven development, use MCP-native data providers (financialdatasets.ai recommended). Free sources like yfinance may have gaps, delays, or inaccuracies.

Why Python over TypeScript for quant work:

• Vectorized calculations (NumPy) vs manual loops
• Pydantic catches validation errors at boundaries
• streamlit run app.py vs npm/webpack complexity
• Division by zero: np.divide(..., where=b!=0) vs manual guards everywhere

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Example Projects

Project	Style	Key Libraries	Data Source
DCF Valuation Tool	Damodaran	numpy-financial	financialdatasets.ai
Portfolio Optimizer	Markowitz	PyPortfolioOpt, scipy.optimize	Professional feed
Factor Research	Open Source AP	pandas, statsmodels, alphalens	WRDS, CRSP
Risk Dashboard	VaR/CVaR	scipy.stats, matplotlib	Professional feed
Data Pipeline	ETL	pandas, SQLAlchemy	Multiple sources

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Getting Started

1. New project: /finance-driver:init or just describe what you want to build
2. Existing project: /finance-driver:status to see where you are
3. Stuck? Tell me the finance problem you're solving — we'll figure it out together

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Iron Laws (Never Break These)

Stage	Iron Law
DEFINE	NO BUILDING WITHOUT 分头研究 FIRST
REPRESENT	PLAN THE UNIQUE PART — DON'T REINVENT
IMPLEMENT	SHOW DON'T TELL — BUILD AND RUN IT
VALIDATE	CROSS-CHECK YOUR INSTRUMENTS — four checks, every time
EVOLVE	SELF-CONTAINED DELIVERABLE
REFLECT	CAPTURE WHAT DIDN'T WORK