🔍 Read the full analysis: New To A Codebase? Let An AI Agent Help You Explore It on ThorstenMeyerAI.com
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TL;DR
A guide published by ThorstenMeyerAI.com on October 19 describes how Reverse Engineer Anything (REA) can help coding agents investigate existing software and turn observed behavior into specifications. Its examples include a local accounting app whose author reported matching selected QuickBooks Desktop reports to the cent; the result is a case study, not an independent evaluation of REA.
ThorstenMeyerAI.com published a guide on October 19 to using the open-source Reverse Engineer Anything (REA) project with coding agents to inspect existing software. The report presents REA as a way to gather evidence about how a program behaves before building a replacement or documenting its rules, while stressing that agent findings need verification and that local analysis does not mean data stays private from the model provider.
The article describes REA as a toolkit combining a local Model Context Protocol (MCP) server, a command-line utility and an agent skill. Coding agents such as Claude Code, Codex, Cursor and Gemini CLI can call its analysis tools. The project supports several kinds of targets, including native applications, JavaScript and Electron apps, .NET and Android software, firmware, network captures, WebAssembly and SQLite databases. For websites, the guide says, it can observe activity in 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. According to the article, the developer used REA 6.4.0 and Ghidra to examine selected behavior in a QuickBooks Desktop for Mac 2024 trial, including inventory calculations, budget sign conventions, reconciliation balances and cash-basis reporting. The developer said Ledger Reborn’s profit-and-loss statement, balance sheet and trial balance matched the official sample company’s figures account by account, to the cent. This is a claim reported by the guide; the material provided does not include an independent replication.
The guide recommends asking narrow, decision-focused questions rather than asking an agent to explain an entire program. It suggests requiring the agent to separate what it observed from what it inferred or could not determine, and to walk through a concrete example with inputs and outputs. It also advises checking that the agent actually called REA tools; an answer produced without tool use may be a model’s unsupported guess.
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.
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From Software Behavior to Specifications
For developers working with unfamiliar or poorly documented software, the method described could help turn observed behavior into specific implementation requirements. Rather than copying screens, an investigator can ask what data is stored, how a calculation is made and which conditions alter the result. That matters when replacing a legacy tool, building an integration or trying to reproduce a business rule whose consequences appear in reports or balances.
The guide also puts limits on the promise. An agent’s explanation is only useful if its evidence is sound: the article advises testing one complete example and labeling claims as observed, inferred or unknown. And because the agent receives analysis results, the data practices of its model provider remain relevant even when REA runs locally.
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How REA Connects to Coding Agents
REA is identified in the source as an MIT-licensed project on GitHub under the repository name morluto/rea. The article reports that version 6.7.0 was released on October 18, one day before the guide, and gives approximate GitHub figures of 325,000 stars and 82,000 forks as of October 19. Those counts are time-specific figures from the source, not a measure of tool accuracy.
The guide says setup requires Node.js 22.19 or newer; native program analysis may also require a disassembler such as Ghidra, or licensed software such as Hopper or IDA. It recommends running the project’s diagnostic command and then checking the connection from inside the agent. The diagnostic checks installation files and prerequisites, the source notes, but does not confirm a live agent connection.
Its safety warning is direct: REA is not a sandbox. Analysis tools run on the user’s machine with that user’s permissions, so unknown programs should be treated as untrusted files. The guide also distinguishes local analysis from data handling by the agent and its model provider: results are passed to the agent, and provider policies apply.
“This is not a sandbox.”
— ThorstenMeyerAI.com, describing REA’s safety limits
software reverse engineering software
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Limits of the Reported Results
The supplied material does not provide an independent test of REA or the reported Ledger Reborn comparison. It does not specify the full test procedure, the exact QuickBooks outputs compared, or whether other users have reproduced the account-by-account results. The reported GitHub counts are also presented without a linked measurement method in the material supplied.
It is not clear from the source how well REA performs across every supported software type, how often its analysis can resolve ambiguous behavior, or what additional checks are needed for safety-critical or financial applications. The article’s example illustrates a possible workflow; it does not establish that an AI agent can reliably reverse-engineer any program or produce a correct replacement without human review.
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Verify the Tool Before Investigating
The guide’s immediate next step for readers is to install REA only after reviewing its setup plan, confirm prerequisites, restart the coding agent and verify that the connection is live. It recommends beginning with a harmless application the user owns, then asking a bounded question and checking the answer against a concrete example.
Further evidence would be needed to judge how broadly the accounting comparison can be reproduced and how REA performs on other kinds of software. Until then, the reported case should be read as a documented example of an investigative workflow, not a general guarantee of accurate results.
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Key Questions
What is Reverse Engineer Anything?
REA is an open-source toolkit that connects coding agents to tools for inspecting existing programs. The source describes it as an MCP server, command-line tool and agent skill.
What did the Ledger Reborn example show?
The guide says a developer investigated selected QuickBooks Desktop behavior and built a local accounting app. The developer reported that three reports for the official sample company matched to the cent; the supplied material does not provide an independent replication.
Does REA keep analysis data entirely on my machine?
Not necessarily. The source says REA performs analysis locally, but results go to the coding agent and may also reach its model provider, subject to that provider’s data policy.
Is it safe to inspect an unknown program with REA?
The guide warns that REA is not a sandbox and its analysis tools run with the user’s permissions. It advises treating unknown programs as untrusted files.
How can I tell whether the agent actually used REA?
Run the project’s installation checks, then confirm within the agent that REA tools are available and being called. The source says the diagnostic checks files and prerequisites, but does not by itself confirm a live connection.
Source: ThorstenMeyerAI.com
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