π‘ Summary
The Australian Tax Optimizer is an AI platform that analyzes Xero data to recover missed tax benefits.
π― Target Audience
π€ AI Roast: βPowerful, but the setup might scare off the impatient.β
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); API keys/tokens handling and storage; dependency pinning and supply-chain risk. Run with least privilege and audit before enabling in production.
π¦πΊ Australian Tax Optimizer
AI-Powered Tax Recovery & Compliance Platform
Recover $200K-$500K in missed tax benefits per client through forensic Xero analysis
Getting Started β’ Documentation β’ API Reference β’ Architecture
π― What is ATO?
The Australian Tax Optimizer is an AI-powered platform that connects to your Xero accounting data (read-only) and performs forensic analysis to identify:
| Recovery Area | Potential Savings | Legislation | |--------------|-------------------|-------------| | π¬ R&D Tax Incentive | Up to 43.5% offset | Division 355 ITAA 1997 | | π Unclaimed Deductions | Variable | Section 8-1 ITAA 1997 | | π° Carry-Forward Losses | Tax offset on profits | Subdivision 36-A | | π¦ Division 7A Compliance | Avoid deemed dividends | Division 7A ITAA 1936 | | π FBT Optimisation | Reduce FBT liability | FBTAA 1986 |
π Architecture
flowchart TB subgraph Client["π₯οΈ Client Layer"] UI[Next.js Dashboard] Reports[PDF/Excel Reports] end subgraph API["β‘ API Layer"] Auth[OAuth 2.0 Auth] Audit[Audit Endpoints] Xero[Xero Proxy] end subgraph Core["π§ Core Engine"] AI[Gemini AI Analyzer] RND[R&D Engine] DED[Deduction Engine] LOSS[Loss Engine] DIV7A[Division 7A Engine] end subgraph Agents["π€ Agent Fleet"] A1[Tax Law Analyst] A2[Xero Auditor] A3[R&D Specialist] A4[Deduction Optimizer] end subgraph Data["πΎ Data Layer"] SB[(Supabase)] XeroAPI[Xero API] Cache[Transaction Cache] end subgraph Validation["β Validation"] V1[Tax Calc Validator] V2[R&D Eligibility] V3[FY Validator] end UI --> Auth UI --> Audit Auth --> XeroAPI Audit --> AI AI --> RND & DED & LOSS & DIV7A RND & DED & LOSS & DIV7A --> Agents Agents --> SB XeroAPI --> Cache --> SB AI --> V1 & V2 & V3 Reports --> SB style AI fill:#4285F4,color:#fff style SB fill:#3FCF8E,color:#fff style XeroAPI fill:#13B5EA,color:#fff
β¨ Features
π Forensic Analysis
- AI-powered transaction scanning
- Pattern recognition for R&D activities
- Misclassification detection
- Multi-year analysis (FY2020-25)
π‘οΈ Enterprise Security
- Read-only Xero access
- AES-256-GCM token encryption
- Multi-tenant isolation
- Row-level security (RLS)
π€ 16 Specialised Agents
- Tax Law Analyst
- R&D Tax Specialist
- Deduction Optimizer
- Loss Recovery Agent
- Division 7A Compliance
- And 11 more...
π Validation System
- 10 specialised validators
- 90-95% confidence scores
- Automatic fix instructions
- Compliance verification
π€ Multi-Agent Development Framework
This project employs a sophisticated multi-agent development framework that coordinates 4 specialist agents plus an orchestrator for structured, quality-gated development.
Agent Fleet
Framework Agents (Development Process):
- π― Orchestrator - Task decomposition, work distribution, results synthesis, quality control
- ποΈ Specialist A: Architect - System design, API schemas, database ERDs, architecture decision records (ADRs)
- π» Specialist B: Developer - Production code implementation, feature development, refactoring
- π§ͺ Specialist C: Tester - Unit/integration/E2E testing, QA, coverage reports (β₯80% target)
- π Specialist D: Reviewer - Code review, technical documentation, API docs, user guides
Tax Domain Agents (Business Logic):
- 18 specialized agents for Australian tax analysis (R&D, deductions, losses, Division 7A, etc.)
- See .agent/AGENTS.md for complete agent registry
Development Workflow
graph TD A[π¨βπΌ Developer] -->|Requirement| B[π Senior PM] B -->|Create Linear Issue| C[π― Orchestrator] C -->|Decompose & Assign| D[ποΈ Specialist A: Design] C -->|Decompose & Assign| E[π» Specialist B: Implement] C -->|Decompose & Assign| F[π§ͺ Specialist C: Test] C -->|Decompose & Assign| G[π Specialist D: Document] D -->|Handoff Context| E E -->|Handoff Context| F F -->|Handoff Context| G G -->|Integrate Results| C C -->|Review & Report| B B -->|Approve & Deploy| A style A fill:#FFB74D,color:#000 style B fill:#4FC3F7,color:#000 style C fill:#BA68C8,color:#fff style D fill:#81C784,color:#000 style E fill:#64B5F6,color:#000 style F fill:#FFD54F,color:#000 style G fill:#A1887F,color:#fff
Quality Gates
Every phase transition requires passing automated quality gates:
| Gate | Criteria | Blocks Phase | |------|----------|--------------| | β Design Complete | ADR created, diagrams complete, risks documented | Implementation | | β Implementation Complete | Code compiles, linting passes, basic functionality works | Testing | | β Testing Complete | β₯80% coverage, all tests pass, no critical bugs | Documentation | | β Documentation Complete | API docs, changelog updated, examples provided | Integration | | β Integration Complete | All outputs merged, system functional, no conflicts | Final Approval | | β Final Approval | PM + Developer sign-off, ready for deployment | Deployment |
See lib/agents/quality-gates.ts for automated enforcement.
Linear Integration
All development work is tracked in Linear with automated updates:
- π Task Creation - Parent issues created from Developer requests
- π Sub-Task Assignment - Specialists automatically assigned via Linear sub-issues
- π Real-Time Updates - Status transitions (pending β in-progress β review β done)
- π« Blocker Escalation - Automatic escalation with @mentions in comments
- π Progress Tracking - Daily reports showing specialist workload and velocity
Quick Commands:
npm run agent:orchestrator -- --task "Add feature" --priority High npm run agent:daily-report # View daily status npm run agent:quality-gate -- --gate <name> # Check quality gate npm run linear:sync # Sync with Linear npm run linear:report # Generate comprehensive report
See MULTI_AGENT_ARCHITECTURE.md for complete framework specification.
π Quick Start
- Node.js 20.x or higher
- npm 10.x or higher
- Xero Developer Account
- Supabase Project
- Google AI API Key (for Gemini)
# Clone the repository git clone https://github.com/CleanExpo/ATO.git cd ATO # Install dependencies npm install # Copy environment template cp .env.example .env.local # Configure your environment variables (see below)
# Supabase (Required) NEXT_PUBLIC_SUPABASE_URL=https://your-project.supabase.co NEXT_PUBLIC_SUPABASE_ANON_KEY=your-anon-key SUPABASE_SERVICE_ROLE_KEY=your-service-role-key # Xero OAuth (Required) XERO_CLIENT_ID=your-xero-client-id XERO_CLIENT_SECRET=your-xero-client-secret XERO_REDIRECT_URI=https://your-domain.com/api/auth/xero/callback # Google AI (Required for analysis) GOOGLE_AI_API_KEY=your-gemini-api-key # Security (Required for production) TOKEN_ENCRYPTION_KEY=your-32-byte-hex-key # Generate: openssl rand -hex 32
# Run migrations via Supabase Dashboard SQL Editor # Or use the migration script: npm run db:migrate
Migration files are located in supabase/migrations/.
# Development npm run dev # Production build npm run build npm start # Run tests npm test
π Documentation
| Document | Description | |----------|-------------| | CLAUDE.md | AI development guidelines (RTCC pattern) | | MULTI_AGENT_ARCHITECTURE.md | Multi-agent framework specification | | spec.md | Technical specification | | API_DOCUMENTATION.md | Complete API reference | | FORENSIC_AUDIT_GUIDE.md | User guide for audits | | AGENTS_README.md | Agent system documentation | | DATABASE_MIGRATIONS.md | Migration instructions |
π§ͺ Testing
# Run all tests npm test # Run with coverage npm run test:coverage # Run specific test file
Pros
- AI-driven analysis for accurate tax recovery
- Comprehensive coverage of various tax incentives
- User-friendly interface for business owners
- Strong security measures for sensitive data
Cons
- Requires integration with Xero, limiting user base
- Dependence on external APIs for functionality
- Complex setup process for new users
- Potentially high costs for small businesses
Related Skills
pytorch
SβIt's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.β
agno
SβIt promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.β
nuxt-skills
SβIt's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.β
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author CleanExpo.
