# Requirements Traceability System - Executive Summary

## Vision

Build a **modern, graph-based requirements traceability system** that enables spec-driven development across all project types (software, hardware, smart contracts, systems engineering) with native support for multiple languages, AI agents, and temporal versioning.

## Problem Statement

Current requirements management tools are:
- **Expensive**: DOORS, Polarion cost $$$
- **Monolithic**: Web-based, not CLI-native
- **Inflexible**: Hard to customize for specific domains
- **Isolated**: Separate from development workflows
- **Limited**: No smart contract support, no AI integration
- **Centralized**: Require server infrastructure

## Solution

A **lightweight, open-source, graph-native requirements traceability system** that:
- ✓ Works offline (SQLite-based)
- ✓ Integrates with dev workflows (CLI-first)
- ✓ Supports all project types (extensible)
- ✓ Enables AI automation (MCP integration)
- ✓ Provides temporal versioning (audit trail)
- ✓ Scales from solo projects to enterprises

## Key Differentiators

| Feature | Impact |
|---------|--------|
| **Graph-based** | Complex queries, impact analysis, visualization |
| **Temporal versioning** | Historical analysis, compliance audits |
| **Multi-language** | Native CLI for Python/Go/Rust/TS |
| **Smart contracts** | First-class blockchain support |
| **Spec-driven** | Unified spec → implementation → test |
| **AI-ready (MCP)** | Autonomous requirement management |
| **Offline-first** | Works without server, version-controlled |

## Architecture Highlights

### Three-Layer Design
1. **CLI Layer**: Typer + Rich (beautiful, type-safe)
2. **Service Layer**: Business logic (reusable, testable)
3. **Storage Layer**: Pluggable adapters (SQLite, Neo4j, File)

### Graph Model
- **Nodes**: Epic, Feature, Story, Task, Test, Code, UI, Spec
- **Edges**: decomposes_to, implements, tests, validates, references
- **Attributes**: Status, priority, owner, version, timestamps

### Temporal Data
- Bi-temporal model (valid_from, valid_to)
- Point-in-time queries
- Requirement evolution tracking
- Compliance audit trail

## MVP Scope (Phase 1)

### Deliverables
- SQLite schema with temporal support
- Pydantic models for all requirement types
- CRUD operations (create, read, update, delete)
- Basic linking (parent-child, implementation)
- CLI commands (Typer)
- Versioning system
- 90%+ test coverage

### Timeline
- **Week 1-2**: Core data model + storage
- **Week 3-4**: Services + CLI commands
- **Week 5-6**: Testing + documentation
- **Week 7-8**: Release v1.0

## Phase 2-5 Roadmap

### Phase 2: Integration
- Code extraction (Python/Go/Rust/TS)
- Test case linking
- Compiler/linter hooks
- Export to RTM format

### Phase 3: Multi-Language
- Go CLI wrapper
- Rust CLI wrapper
- TypeScript CLI wrapper
- Language-specific extractors

### Phase 4: Advanced Features
- TUI (Textual)
- Neo4j support
- Smart contract integration
- Visualization

### Phase 5: AI & Automation
- MCP server
- AI agent integration
- Autonomous requirement decomposition
- Automated linking

## Technology Stack

| Layer | Technology | Rationale |
|-------|-----------|-----------|
| **Storage** | SQLite | Portable, versioned, lightweight |
| **CLI** | Typer + Rich | Type-safe, beautiful |
| **TUI** | Textual | Full-featured, reactive |
| **Models** | Pydantic | Schema validation, JSON schema |
| **Testing** | pytest | Standard, comprehensive |
| **Packaging** | Poetry/uv | Dependency management |

## Success Metrics

### Year 1
- 1000+ GitHub stars
- 50+ contributors
- 10+ language integrations
- <100ms queries on 10k requirements
- 4.5+ rating on package managers

### Year 2
- 10k+ active users
- 100+ integrations
- Enterprise adoption
- Compliance certifications

## Market Opportunity

### Target Markets
1. **Agile Teams** (50k+ teams)
2. **Systems Engineering** (10k+ teams)
3. **Smart Contract Dev** (5k+ teams)
4. **AI-Driven Development** (Growing)
5. **Regulatory Compliance** (10k+ teams)

### Total Addressable Market
- **TAM**: $5B+ (requirements management market)
- **SAM**: $500M+ (open-source + lightweight segment)
- **SOM**: $50M+ (year 1-3 realistic)

## Competitive Advantages

1. **Open Source**: No vendor lock-in
2. **Graph-Native**: Superior query capabilities
3. **Temporal**: Compliance-ready
4. **Multi-Language**: Developer-friendly
5. **Smart Contracts**: Unique positioning
6. **AI-Ready**: Future-proof
7. **Offline-First**: Privacy-conscious

## Next Steps

1. **Approve MVP scope** (this document)
2. **Setup project structure** (GitHub repo)
3. **Begin Phase 1 development** (Week 1)
4. **Establish community** (Discord/GitHub Discussions)
5. **Plan Phase 2 features** (Week 4)

## Questions & Discussion

- Should we start with Python-only or multi-language MVP?
- SQLite or Neo4j for initial release?
- Open source license preference (MIT/Apache)?
- Community platform (Discord/Slack)?
- Funding/sponsorship strategy?

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**Status**: Ready for implementation
**Owner**: [Your Name]
**Last Updated**: 2025-11-20

