TAO Delegation Portfolio Optimizer

A comprehensive tool for analyzing Bittensor validators and subnets to generate optimized delegation portfolios with emphasis on capital preservation and sustainable TAO accumulation.

Background

Following the Tenex (SN67) exit scam that resulted in $2.8M in delegator losses, this tool prioritizes credibility assessment and security verification before yield optimization.

Features

• Credibility Scoring: Multi-factor analysis of team transparency, audits, security, utility, and community health
• Real APY Data: Integration with dTao API endpoints for accurate yield information
• Portfolio Construction: Automated diversification across tiers (Core, Growth, Opportunistic)
• Risk Management: Red flag detection and automatic exclusion of suspicious subnets
• Growth Projections: Conservative, moderate, and optimistic scenario modeling

Quick Start

Prerequisites

pip install -r requirements.txt

Setup

# 1. Copy environment template and add your API key
cp .env.example .env
# Edit .env with your Taostats API key

# 2. Source environment variables
source .env

Usage

# 1. Fetch latest data from Taostats API
python3 fetch_data.py

# 2. Run portfolio analysis
python3 analyze_portfolio.py

Output Files

File	Description
tao_delegation_report.md	Comprehensive analysis report
credibility_analysis.json	Structured credibility data
portfolio_allocation.json	Portfolio recommendation

Sample Portfolio Output

For a 175 TAO wallet (as of January 2026):

Tier	Validator	Subnet	APY	Credibility	Allocation
Core	Polychain	Nineteen.ai (SN19)	79.0%	A- (80)	50 TAO
Core	Taostats	Lium.io (SN51)	58.8%	A- (82)	50 TAO
Growth	Unknown	Templar (SN3)	371.3%	B+ (77)	35 TAO
Growth	Tensorplex Labs	Nineteen.ai (SN19)	87.9%	A- (80)	17.5 TAO
Opportunistic	Unknown	Hone	144.2%	C (45)	17.5 TAO

Blended APY: 140.9% | Subnets Used: 4

Note: APY rates are highly variable and reflect current market conditions.

Credibility Scoring Methodology

Score = (Team × 20%) + (Audit × 25%) + (Security × 25%) + (Utility × 15%) + (Community × 15%)

Scoring Components

Component	Weight	What We Verify
Team Transparency	20%	Doxxed founders, corporate registration
Code Audit	25%	Security audits by Bitsec or equivalent
Smart Contract Security	25%	Timelocks, multisig, upgrade mechanisms
Utility Verification	15%	Real product usage, revenue, partnerships
Community Health	15%	Discord activity, response times

Red Flag Penalties

• Exit scam indicators: Total exclusion (score = 0)
• Single owner + no timelock: 70% penalty
• Multiple red flags: 40% penalty

Portfolio Construction Rules

Diversification Requirements

• Maximum 40% per validator
• Maximum 50% per subnet
• Minimum 3 different subnets

Tier Allocation

• Core (60%): Credibility >= 75 - Capital preservation focus
• Growth (30%): Credibility 60-75 - Balanced risk/reward
• Opportunistic (10%): Credibility 45-60 - Higher yield potential

API Reference

Uses Taostats API with the following endpoints:

Endpoint	Purpose	Records
/api/subnet/latest/v1	Subnet metadata with emission/flow metrics	~129
/api/validator/latest/v1	Validator profiles	~75 (paginated)
/api/dtao/validator/yield/latest/v1	Real APY data	~6,100 (paginated)
/api/dtao/pool/latest/v1	Pool pricing & sentiment metrics	~129
/api/dev_activity/latest/v1	GitHub activity	~115 (paginated)

Note: The fetch_data.py script handles pagination automatically to ensure complete data retrieval.

Critical Exclusions

Subnet	Status	Reason
Tenex (SN67)	EXCLUDED	Exit scam - $2.8M stolen
oneoneone (SN111)	Avoid	Insufficient track record
Graphite (SN43)	Monitor	High APY variance

Project Structure

TAO/
├── fetch_data.py              # Data collection script (with pagination)
├── analyze_portfolio.py       # Main analysis engine
├── requirements.txt           # Python dependencies
├── .env.example               # Environment template
├── credibility_analysis.json  # Credibility data output
├── portfolio_allocation.json  # Portfolio recommendation output
├── CLAUDE.md                  # Claude Code context
├── README.md                  # This file
└── data/
    ├── subnets_latest.json    # 129 subnets with flow metrics
    ├── validators_latest.json # 75 validators (paginated)
    ├── validator_yield.json   # 6,100+ APY records (paginated)
    ├── subnet_pools.json      # Pool pricing & sentiment
    └── github_activity.json   # 115 dev activity records

Safety Disclaimer

This tool provides analysis and recommendations only. Always verify information independently before delegating TAO. The cryptocurrency space carries inherent risks including but not limited to:

• Smart contract vulnerabilities
• Team/project failures
• Market volatility
• Regulatory changes

Never delegate more than you can afford to lose.

Contributing

Contributions welcome! Areas for improvement:

• Historical APY tracking
• Automated monitoring alerts
• Validator uptime integration
• Additional credibility data sources
• Backtesting framework

License

MIT License

Acknowledgments

• Taostats for API access
• Bitsec (SN60) for ecosystem security work
• Bittensor community for transparency and research support