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Etherscan Launches Transaction Debugger for AI Agents

The new tool enables AI agents to analyze and decode EVM transaction calls using real-time data.

Updated on Oct. 16, 2026 in Artificial Intelligence

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Etherscan has launched a new transaction debugger in its Build with AI suite, designed to help autonomous agents decode Ethereum blockchain transaction paths. AI Illustration. Upload story photo >

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Etherscan has introduced a new Transaction Debugger skill to its Build with AI suite, allowing automated agents to decode Ethereum Virtual Machine (EVM) transaction paths. The tool is designed to provide AI agents with live data, helping to reduce the risk of hallucinations by ensuring accurate transaction reconstruction.

Why it matters

By integrating live blockchain data into agent environments, this tool enables AI to perform reliable security analysis and transaction troubleshooting. This direct access to technical data helps developers build more autonomous and accurate agents for decentralized finance operations.

The debugger operates across more than 60 EVM-compatible chains using direct API data for read-only reconstructions. It supports two distinct reporting modes, Simple and Security, and allows users to compare two transactions simultaneously.

The players

Etherscan

Etherscan is a leading blockchain explorer and analytics platform that provides detailed data for the Ethereum network and other EVM-compatible chains.

The details

Developers can integrate the debugger into agent environments via an npx command. The tool tracks asset movements and contract permissions, providing granular failure analysis for transactions that do not execute successfully.

Timeline

  1. August 2026: The Build with AI suite was launched.

  2. September 4, 2026: Public promotion of the debugger began.

  3. October 16, 2026: Additional guidance for the debugger was published.

The Tech Race

This release marks an expansion of the functional capabilities provided by the Build with AI suite. By providing agents with real-time diagnostic tools, Etherscan is positioning its infrastructure to become the standard data layer for autonomous blockchain agents.

Developers building AI agents can now implement standardized, accurate debugging to streamline their development workflows. This capability reduces the time required to diagnose failed transactions and enhances the reliability of automated financial interactions.

The takeaway

Developers should prioritize using tools that connect AI directly to blockchain state rather than relying on cached or potentially outdated datasets. Implementing live reconstruction tools like the Transaction Debugger is essential for building agents that function reliably in complex decentralized environments.

Further reading

Learn more about the latest innovations in the Artificial Intelligence sector.

More information

Access documentation and implementation details in the Etherscan skills repository.

Source note: This article includes information reported by Crypto Briefing.

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Do you trust AI agents to accurately analyze financial data without direct human supervision?