WalletFollow publishes a sourced research library for wallet and copy-trading analysis

WalletFollow’s public knowledge base is now available from the site footer. It covers how to read a Hyperliquid wallet, interpret performance measures, assess copy-trading risk and use AI to organize research. Each guide includes a direct answer, supporting explanations, related reading and links to the primary documentation behind its factual claims.

Start with the measure you need to understand

A trader’s account value, realized profit and mark-to-market performance answer different questions. The library explains why a single headline number is insufficient for evaluating a wallet. Readers can follow the topic links from a definition to the practical questions that matter when comparing a strategy’s history, leverage and concentration.

The blog adds longer research workflows. These articles focus on the sequence of checks a reader can make rather than a list of supposedly profitable wallets. Historical observations and examples should help readers examine the evidence; they are not promises that another account will reproduce the same result.

AI data access: what is available

The Data API is available with account-based credentials, documented plans and quotas. Its documentation is public. The native MCP connector, CLI and client plugins remain planned, and the AI integration page identifies that status. The Data API supplies research data; it is not a trading API.

• Use the knowledge base to check a definition, calculation basis or research limitation.
• Use the Data API documentation to evaluate the currently available data interface.
• Use the AI and MCP page to distinguish present data access from planned connectors.
• Treat copy-trading setup and any account approvals as a separate product workflow.

The newsroom follows the same sourcing approach: protocol updates link to the original announcement, and documentation analysis is labelled as analysis. Publication dates refer to our own coverage. Source dates and the last source check are shown separately so a newly published explainer does not make an older event appear to have happened today.