🔍 Read the full analysis: How To Use An AI Agent To Explore Software You Didn’t Write on ThorstenMeyerAI.com
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TL;DR
A ThorstenMeyerAI.com report published October 19 describes how Reverse Engineer Anything (REA) lets coding agents use local software-analysis tools to investigate programs developers did not write. Its examples show how focused questions and verification can turn observations into a software specification, but the report’s accounting-app results come from a developer case study, not an independent validation.
A report published October 19 describes how Reverse Engineer Anything (REA), an open-source toolkit, connects AI coding agents to analysis tools that can inspect existing software. The approach is intended to help developers answer focused questions about how a program behaves before they design a replacement or compatible feature; the report’s strongest example, an accounting app matched against QuickBooks Desktop outputs, is a developer’s own case study rather than an independently verified result.
REA combines a local MCP server, a command-line utility and an agent skill that guides investigations. The report says agents including Claude Code, Codex, Cursor and Gemini CLI can use it. Depending on the target, the toolkit draws on analysis tools for native programs, Electron and JavaScript apps, .NET and Android software, firmware, saved network traffic, WebAssembly and SQLite databases. It can also observe behavior in a browser controlled by the user.
The report recommends starting with a question that is narrow enough to answer, such as how a partial invoice payment changes the balance and which account receives the posting. The agent should identify stored data, calculations and conditions that affect the result, while labeling findings as observed, inferred or unknown. A useful test of the answer is whether the agent can explain one concrete example with inputs and outputs, rather than merely describing a screen.
For setup, the report gives a guided installer command, npx rea-agents@latest setup, and says Node.js 22.19 or newer is required. Some native-program investigations also need tools such as Ghidra, Hopper or IDA. It advises restarting the coding agent and checking that REA tools actually load before relying on an answer. The project’s diagnostic command checks setup files and prerequisites, but the report says it does not verify the live agent connection; users should confirm that separately inside the agent.
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 inheriting an unfamiliar codebase or replacing a tool, the hard problem is often not reproducing its interface but identifying the rules behind its outputs. A focused investigation can help turn behavior into a testable specification: what is stored, how a calculation works and which conditions change it. That may reduce reliance on guesswork when building integrations, migration tools or replacement applications.
The report’s accounting example illustrates the potential but should be read with care. Its author says they used REA to investigate QuickBooks Desktop for Mac 2024 and then built Ledger Reborn, whose profit-and-loss statement, balance sheet and trial balance reportedly matched Intuit’s sample company account by account, to the cent. Those results are reported by the project’s author; the supplied material does not include independent testing. REA can provide evidence for an investigation, but an agent’s conclusions still need review and validation against the program’s actual behavior.
There is also a data and security trade-off. REA performs analysis locally, according to the report, but its findings are passed to the connected AI agent and may reach the model provider under that provider’s data policy. Local analysis does not mean the entire workflow stays on the user’s machine.
software reverse engineering toolkit
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How REA Fits Into Agent Work
REA is identified in the report as an MIT-licensed open-source project hosted on GitHub under morluto/rea. The report says version 6.7.0 was released October 18, 2026, and describes the project as having gained attention on GitHub’s trending page earlier that month. It also gives approximate GitHub counts as of October 19: 325,000 stars and 82,000 forks. These are dated observations, not measures of accuracy or adoption quality.
The toolkit gives an agent access to external analysis utilities through MCP, a protocol for connecting agents with tools. That connection does not make the agent’s answer inherently reliable. As the report’s workflow emphasizes, users need to verify that the tools were called, distinguish direct observations from inferences, and ask for examples they can check. The source also cautions that REA is not a sandbox: opening an untrusted program exposes it to analysis tools running with the user’s permissions.
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Limits of the Reported Results
The supplied material does not describe independent testing of REA or Ledger Reborn’s reported accounting matches. It also does not establish how reliably the toolkit performs across its many listed target types, how much manual interpretation different investigations require, or how often an agent’s analysis is mistaken. Those questions cannot be answered from a single case study.
Data handling depends on the connected agent and model provider, according to the report; it does not specify the policies or retention practices of every provider. The report also says REA’s maintainer is anonymous. Users considering the toolkit should check current project documentation, dependencies and provider policies before using it with sensitive software or data.
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Verify Tools Before Investigating
The report’s practical next step is to install REA, review the setup plan, and confirm from inside the coding agent that its tools are available before opening a target. A first inspection should use software the user owns and a narrow behavior question. For sensitive or unfamiliar binaries, users should assess the security risks first; the source explicitly warns that REA is not an isolation environment.
For any conclusions intended to guide a replacement or business-critical feature, developers should compare the agent’s explanation with concrete program outputs and test cases. The report does not identify a forthcoming independent evaluation or other scheduled milestone for REA. Its account of version 6.7.0 is a snapshot from October 19, 2026, so installation instructions and supported tools may change.
software investigation tools for developers
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Key Questions
What is REA?
Reverse Engineer Anything is an open-source toolkit that connects AI coding agents to software-analysis tools through a local server, command-line utility and agent skill, according to the report.
Does REA keep all analysis data local?
No. The report says REA analyzes targets locally, but results go to the connected agent and may also be handled by its model provider under that provider’s data policy.
How can I tell whether my agent is using REA?
Run the project’s setup checks, then confirm inside the agent that it can call an REA tool. The report cautions that the diagnostic command checks files and prerequisites, not the live agent connection.
Does REA prove that an agent’s explanation is correct?
No. REA supplies analysis tools, but the report advises distinguishing observations from inferences and testing whether the agent can explain a concrete example. The reported QuickBooks comparison is a developer case study, not independent verification.
Is it safe to inspect an unknown program with REA?
The source warns that REA is not a sandbox and that analysis tools run with the user’s permissions. Treat untrusted programs cautiously and assess the risks before opening them.
Source: ThorstenMeyerAI.com
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