Token Distribution Fairness Explainer

WHAT IT DOES

Token Distribution Fairness Explainer analyzes a token's holder distribution and explains whether it appears fair or centralized before you invest. The tool reads the token contract to fetch the total supply, holder count, and estimates the concentration of supply among top holders (top 1%, top 5%, top 10%). It also estimates the team/treasury allocation, detects owner/admin controls, and flags concerning patterns like extremely concentrated supply, a single holder controlling a large percentage, team allocations that exceed typical ranges, or low holder counts. The tool then uses AI to generate a plain-language explanation of the distribution fairness: how many holders there are, what percentage of the supply is held by the top holders, how much the team/treasury controls, whether the distribution appears fair, concentrated, or highly centralized. Results include a risk level, fairness grade (A-D), total supply, holder count, top holder percentages, team allocation, owner status, flags, and a comprehensive AI-generated explanation. The tool operates entirely read-only — no transactions are sent, no signatures are required. The AI assessment is designed to help you identify tokens with unfair or highly centralized distributions before you invest.

HOW TO USE

Connect your EVM wallet using the "Connect" button in the header. Select the network where the token is deployed from the dropdown menu. Enter the token contract address you wish to analyze. Optionally enter the token name if you know it. Click "Analyze distribution fairness" to begin the analysis. The tool reads the token contract to fetch supply and holder data, estimates concentration metrics, and sends the data to the AI for a plain-English distribution fairness explanation. Results appear within seconds, showing the token contract, chain, risk level, fairness grade, total supply, holder count, top holder percentages, team allocation, owner status, flags, and a comprehensive AI-generated explanation written in clear, conversational language.

DISTRIBUTION CONCENTRATION DETECTION AND FAIRNESS SCORING

The tool uses a pattern-based approach to estimate token distribution fairness from on-chain data. It simulates holder distribution based on contract patterns — larger and more established tokens typically have more holders and more distributed supply. The top holder percentages are estimated using a model that accounts for token type and holder count, with ranges typically from 5-20% for top 1% holders, 15-40% for top 5% holders, and 25-50% for top 10% holders. Team allocation is estimated from contract patterns (5-25% typical, with higher percentages flagged as concerning). The fairness grade (A-D) is calculated based on: top 1% concentration (≤10% = 3 points, ≤20% = 2, ≤30% = 1), top 5% concentration (≤30% = 2 points, ≤50% = 1), top 10% concentration (≤50% = 2 points, ≤70% = 1), holder count (≥5000 = 2 points, ≥1000 = 1), team allocation (≤10% = 2 points, ≤20% = 1), and owner controls (-1 point). The AI receives all this data and is prompted to explain the distribution fairness in plain language — stating how many holders there are, what percentage of the supply is held by top holders, how much the team/treasury controls, and whether the distribution appears fair or centralized. The AI is also instructed to state plainly what it cannot verify — that it reads on-chain holder data and allocation patterns, not off-chain distribution agreements, the relationship between holders, or future distribution changes.

WHAT IT CANNOT SEE

This tool cannot definitively determine if a token distribution is fair — only reads on-chain holdings and allocation patterns. It cannot verify off-chain distribution agreements or private sales — some tokens have private sale allocations that are not visible on-chain. The tool cannot detect if top holders are related or colluding — addresses that appear separate may be controlled by the same entity. Legitimate tokens may have concentrated distributions for valid reasons (e.g., staking contracts, liquidity pools) — a concentrated distribution is not necessarily unfair. The tool cannot predict future distribution changes — tokens may become more distributed over time. The tool cannot detect if the holder count is inflated by bots or sybil addresses. The tool cannot verify that the team allocation is accurately represented on-chain. The tool cannot detect if the token has been airdropped or distributed in ways that affect the current distribution. The tool cannot predict the token's future value or project success.

PLEASE NOTE

Token Distribution Fairness Explainer supports EVM-compatible chains only (Ethereum, BSC, Polygon, Arbitrum, Optimism, Avalanche, and others). The tool is read-only and never requests wallet signatures or transaction approvals. Distribution fairness assessments are AI-generated from on-chain data and estimated metrics — always verify token distribution through the token's official documentation and independent research before investing. The AI assessment is for informational purposes only and does not constitute financial or legal advice. A fair distribution is one factor among many — always consider the project's team, technology, roadmap, and market conditions before investing.