Solution to the Asset Fragmentation Problem: Unexpectedly Recovering 500U Forgotten Assets

As the market recovers, many investors are showcasing their profits and reporting their results, with FOMO emotions running high. As an investor who has been in the cryptocurrency market for five years, I have learned how to manage my positions and remain calm. Recently, I decided to reduce my holdings and wait for the next pullback opportunity, as I have already reached my expected profit.

In my spare time, I started organizing the scattered wallets. As a veteran, since the DeFi summer of 2020, I have accumulated hundreds of wallet addresses. Most of these addresses were created to participate in early projects, new coin launches, and airdrop activities, and now I can no longer remember their specific uses.

I once seriously created a table to record the usage and asset status of each wallet, but over time, the failure to update in a timely manner led to data becoming invalid. Recently, I tried using a new wallet analysis tool to scan these old addresses.

To my surprise, I found stablecoin LP assets worth about 500U in an old wallet that had not been used for a long time! These assets come from a liquidity mining project I participated in early on, which was later forgotten due to the decline in the project's popularity.

This tool not only identifies the LP assets themselves but also clearly displays the composition of the LP, the liquidity pool, and the number of redeemable stablecoins. Without this automatic scanning and structured display function, I might not think about this fund until the next bull market.

In addition to asset identification, this tool also provides features such as multi-chain wallet asset analysis, interaction record viewing, and the marking of risky addresses and witch behavior. Its performance far exceeded my expectations, providing me with a sense of security in asset traceability.

For ordinary users, this tool that can discover and integrate small fragmentary assets is very practical. Although a single wallet may only have a few dozen dollars, it can accumulate to thousands of dollars.

This type of tool also provides project parties with powerful batch address filtering capabilities. Users can upload txt files to batch import wallet addresses and achieve efficient filtering and analysis through multi-dimensional conditions. The core filtering dimensions supported include wallet creation time, asset holding and exclusion conditions, specified asset holdings, minimum asset thresholds, and contract interaction record filtering.

This batch address filtering function is suitable for a variety of scenarios, such as precise airdrops, community growth analysis, user profile construction, risk address investigation, marketing effectiveness tracking, and identification of old users. It transforms complex wallet data into actionable insights, significantly improving the efficiency and accuracy of Web3 projects in data-driven decision-making.

With the rapid growth of Web3 user behavior data, on-chain information is becoming increasingly rich. However, most protocols are still at the stage of judging users solely based on their balances, which makes it difficult to effectively identify the real value and risks behind the addresses, and to achieve more inclusive financial services.

The core objective of this new type of tool is to build an AI-driven on-chain identity authentication and credit scoring system, promoting the development of Web3 finance from heavy collateral and heavy KYC towards a direction focused on no collateral and behavior.

Currently, these tools support features such as multi-dimensional behavior analysis of single addresses, bulk address filtering, risk interaction detection, and a reputation tagging system. In the future, they will also integrate credit scoring and issue credit NFTs.

From the underlying data engine, AI scoring model, to credit NFTs and behavior incentive systems, the modular architecture of these tools will serve the entire Web3 application ecosystem, including decentralized lending, DAO governance, anti-witch airdrops, reputation-driven incentive mechanisms, identity systems, and GameFi strategies.

For ordinary users, these tools can help recover forgotten assets, organize wallet behaviors, and avoid potential risks. For project teams or developers, they are the best assistants for precise airdrops, user screening, behavior modeling, and credit incentives.

The future Web3 not only requires asset-holding addresses but also trustworthy addresses. These emerging tools are providing infrastructure support for this trust revolution. Sometimes, a useful on-chain tool can help you recover a forgotten asset, or even discover that a token you once held has significantly appreciated, making you an unwitting millionaire!