🔍 Read the full analysis: What Happens When You Ask An AI Agent To Explore A Codebase? on ThorstenMeyerAI.com
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TL;DR
A report published by ThorstenMeyerAI.com on Oct. 19 describes how Reverse Engineer Anything, or REA, lets coding agents investigate existing software using analysis tools. Its Ledger Reborn example reports that a developer used REA to study QuickBooks Desktop and build an accounting app whose reports matched an official sample company to the cent; that result is the author’s account, not an independently verified finding here. The piece also warns that agent output must be checked and that REA is not a sandbox.
A report published by ThorstenMeyerAI.com on Oct. 19 describes how developers can use Reverse Engineer Anything (REA) to direct AI coding agents to inspect existing software, rather than guess how it works from its interface. The article points to a developer’s QuickBooks Desktop investigation as an example, while stressing that useful results depend on narrow questions, a working tool connection and checks against evidence.
REA is an open-source project that connects coding agents to software-analysis tools. The source describes three components: a local Model Context Protocol (MCP) server that agents can call, a command-line program for setup and analysis, and an agent skill that guides investigations. Supported targets span native applications, Electron and JavaScript programs, .NET and Android apps, firmware, databases and other formats. For websites, it can observe activity through a browser controlled by the user.
The report’s central example is Ledger Reborn, a local accounting application built after its developer investigated QuickBooks Desktop for Mac 2024. According to the source, the developer used REA 6.4.0 and Ghidra to examine specific rules, including inventory calculations, budget sign conventions, reconciliation balances and cash-basis reporting. The author says Ledger Reborn’s profit-and-loss statement, balance sheet and trial balance matched the official QuickBooks sample company account by account, to the cent. That is a reported project result; the article does not provide independent verification of it.
The guidance is to ask about one behavior at a time, state what decision the investigation will inform, and ask the agent to distinguish observed evidence from inference and unknowns. A useful test is whether it can explain a complete example with concrete inputs and outputs. If it only describes screens, or answers without calling REA tools, the agent may be relying on guesses rather than inspecting the target.
Infographic 01 · Reverse Engineer Anything
Five places to point REA first, and how to tell when the answer is wrong.
REA gives coding agents such as Claude Code and Codex tools to inspect programs, apps and browser sessions. Each investigation needs a finishable question and a check.
npx rea-agents@latest setupThe five investigations
What to ask, and the check that catches a wrong answer.
- 1
Ask a question you can finish
One behaviour, one decision it informs. Example: how a partial payment changes an invoice balance.
It’s wrong ifThe agent can't walk through one concrete example with real inputs and outputs. - 2
Get REA connected and confirmed
Run the guided setup, then doctor, then call binary_session inside the agent before any real target.
It’s wrong ifAnswers arrive without a single REA tool call: you're reading the model's guesses. - 3
Turn a business rule into a spec
Inputs, stored fields, formula, edge cases, plus test cases checked against the original's own output.
It’s wrong ifYour version and the original disagree on a test case, even by one cent. - 4
See what has to survive a copy
Find what an app writes to the clipboard and what it keeps locally, then design your own copy and paste.
It’s wrong ifThe explanation doesn't predict what lands in a plain text editor, an email and your app. - 5
Your own app, your equipment, an old program
Start with software you own or rely on. Ask what it sends, stores or calculates when you do one thing.
It’s wrong ifIt only works for the example you watched. Test with a new file or a read-only command first.
Sources: REA on GitHub (stars via GitHub API, 19 Oct 2026); REA installation guide; REA security policy.
Powered by Thorsten Meyer AI
From Software Behavior to Business Rules
For developers recreating, replacing or integrating with established software, understanding a screen is not enough. A familiar interface can conceal the data model, calculations and conditional rules that determine what happens when a user changes a record or runs a report. The report presents REA as a way to turn those hidden behaviors into a written specification that developers can test and use when building another system.
The distinction matters because AI-generated applications can look plausible while producing incorrect results in real workflows. A tool-assisted investigation may give an agent evidence from the program itself, but it does not make every conclusion reliable. Readers should treat the reported QuickBooks match as an example of what the article’s author says one project achieved, not as a guarantee that REA or an AI agent will reproduce other software accurately.
software reverse engineering tools
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How REA Fits Into Agent Workflows
REA’s role is to make analysis tools available to an agent working on a developer’s machine. The source lists Claude Code, Codex, Cursor and Gemini CLI among the agents it can connect to. It reports that version 6.7.0 was released on Oct. 18 and that the project had about 325,000 GitHub stars and 82,000 forks on Oct. 19. Those figures are dated observations from the source, not measures of accuracy or adoption across all developers.
Setup alone does not establish that the agent can use the tools. The report says REA’s diagnostic command checks installation files and prerequisites, but does not verify a live agent connection. It recommends checking inside the agent that an REA tool is available, then trying an inspection on a harmless program the user owns. Native-program analysis may require a disassembler such as Ghidra, as well as its Java prerequisite, or licensed software such as Hopper or IDA; the source also lists Node.js 22.19 or newer as a requirement.
“This is not a sandbox.”
— Thorsten Meyer, describing REA’s safety limits
Limits, Safety and Verification
The source describes one developer’s case study but does not provide an independent audit of the reported to-the-cent match, the underlying test procedure or a full set of results. It also does not establish how often REA produces correct findings across different software, or how reliably agents separate direct observations from interpretations. Performance will depend on the target program, the available analysis tools and the quality of the questions.
There is also a data and security boundary. REA runs analysis locally, according to the report, but the agent receives results and the model provider may process them under its own data policy. The piece cautions against treating local execution as protection from disclosure. It says REA is not a sandbox and advises handling unknown binaries as untrusted files. The source material provided for this article ends partway through its discussion of the case study, so further findings and qualifications are not available here.
Verify the Agent Before Relying
The report recommends a staged process: choose one behavior and the decision it affects; install REA and review the setup plan; check that prerequisites are present; and confirm that the agent can call an REA tool. Developers can then test a small, trusted program before opening a more complex target. For each finding, they should ask for evidence, a concrete example and a clear distinction between observed, inferred and unknown.
For any project based on another application’s behavior, the next test is to compare the resulting specification and outputs with known cases. The source does not report a new REA release beyond version 6.7.0 or a scheduled follow-up to the Ledger Reborn case study. Further claims about the tool’s accuracy, security or the accounting app’s results would need additional documentation or independent testing.
Key Questions
What is REA?
Reverse Engineer Anything is an open-source toolkit that gives compatible AI coding agents access to software-analysis tools through an MCP server, a command-line program and an agent skill, according to the report.
Does an AI agent automatically understand a codebase after REA is installed?
No. The report recommends asking a focused question, confirming that the agent can call REA tools, and checking whether its answer is supported by a concrete example. A description based only on an interface may not explain the underlying behavior.
Did Ledger Reborn’s reports match QuickBooks?
The source says its developer’s profit-and-loss statement, balance sheet and trial balance matched QuickBooks Desktop’s official sample company account by account, to the cent. That is a claim reported in the article, not an independently verified result in the material provided.
Is REA safe to use on any program?
The report says REA is not a sandbox and that analysis tools run with the user’s permissions. It advises treating unknown binaries as untrusted and notes that results may be sent to the agent and its model provider under that provider’s data policy.
What should developers check after setup?
Check installation files and prerequisites, then confirm from inside the agent that an REA tool is available. The source says REA’s diagnostic command does not itself verify the live connection.
Source: ThorstenMeyerAI.com
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