🔍 Read the full analysis: Point An AI Agent At A Project And Start Learning Its Structure on ThorstenMeyerAI.com
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TL;DR
Reverse Engineer Anything (REA) is an open-source toolkit that lets coding agents inspect existing software and trace specific behaviours. A case study described using it to investigate QuickBooks Desktop and build an accounting app whose statements matched the sample company’s figures, though that result comes from the project’s own account and does not establish broader reliability.
Reverse Engineer Anything (REA), an open-source toolkit for connecting AI coding agents to software-analysis tools, is being presented as a way to investigate how existing programs behave—not just how their screens look. In an October 19 report, Thorsten Meyer described using REA to examine QuickBooks Desktop and develop a separate accounting app, Ledger Reborn, whose key financial statements reportedly matched Intuit’s sample company account by account, to the cent.
REA is hosted on GitHub as morluto/rea and is licensed under the MIT license, according to the report. Its components include a local MCP server that coding agents can call, a command-line utility for setup and analysis, and an agent skill that guides investigations. The report names Claude Code, Codex, Cursor and Gemini CLI as compatible agents. It says version 6.7.0 was released October 18, 2026.
The toolkit brings together analysis tools for different kinds of software, including native applications, Electron and JavaScript programs, .NET and Android apps, firmware, WebAssembly, SQLite databases and older DOS code. For websites, REA can observe activity in a Chrome-family browser under the user’s control. The report says it can use tools such as Ghidra, Hopper or IDA for native-program analysis; some options require separate installation or a paid license.
The QuickBooks example focused on specific accounting behaviours, including inventory calculations, budget sign conventions, reconciliation balances and cash-basis reporting. Meyer says the developer used REA’s findings to build Ledger Reborn, then compared its profit-and-loss statement, balance sheet and trial balance with QuickBooks’ official sample company. The account-by-account, to-the-cent match is reported by the article; the supplied material does not include an independent evaluation of the comparison.
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 Behaviour to Specifications
For developers building replacements, integrations or internal tools, the difficult part is often not reproducing a familiar interface but identifying the rules behind it. An invoice screen, for example, does not show by itself how partial payments affect balances, which accounts receive entries, or how a report changes under different accounting methods. REA’s proposed role is to help an agent gather evidence about those behaviours so a developer can turn them into explicit rules and test cases.
That could make AI-assisted development more useful for complicated, established software, where an agent’s plausible-sounding guess may not reflect actual program behaviour. The report’s practical advice is to ask about one behaviour at a time, request a concrete example, and have the agent label findings as observed, inferred or unknown. The QuickBooks result is an illustration of what one project says it achieved, not proof that REA reliably reconstructs arbitrary software or that every generated replacement will be accurate.
There are also data and security implications. REA runs analysis locally, but the article warns that findings are passed to the AI agent and may also be sent to its model provider under that provider’s data policy. It also quotes the project’s warning that REA “is not a sandbox”: opening an untrusted program can expose it to analysis tools running with the user’s permissions.
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How REA Fits Into Agent Workflows
REA uses the Model Context Protocol (MCP) to let an AI coding agent call external tools. In this setup, the agent can request analysis rather than relying only on information already in its training or on a developer’s description. The report says a guided installer can detect supported agents, present a setup plan for approval and configure the connection. It lists Node.js 22.19 or newer as a requirement.
The report cautions that setup checks do not prove the agent is connected and using REA. Its recommended checks include running the project’s diagnostic command, then asking the agent to call an REA tool and verifying that it responds. A first inspection can target a small application the developer owns. If the agent answers questions about a target without invoking an REA tool, the answer may be a model-generated guess rather than a finding from the analysis.
The article says REA drew attention on GitHub’s trending page in early October. It reports approximately 325,000 stars and 82,000 forks as of October 19, but provides no earlier comparison or measurement window for those counts. The project’s maintainer is described as anonymous.
“REA supplied evidence and imperf…”
— Thorsten Meyer, describing the Ledger Reborn case study
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Limits of the Reported Results
The source gives no independent test of the Ledger Reborn comparison, and the supplied case-study text ends mid-sentence. The reported match with QuickBooks’ sample company should therefore be treated as the article’s account of one developer’s result. It does not establish how well REA performs across other applications, versions, accounting cases or hardware.
It is also unclear from the supplied material how often the toolkit’s analysis is incomplete or incorrect, what review process catches mistakes, and how much specialist knowledge is needed to interpret findings. The report says analysis is local, but agent outputs may reach a model provider; the exact data handling depends on the agent and provider. The source does not provide a detailed comparison of those policies.
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Testing the Tool on Real Projects
The immediate next step for developers interested in REA is to verify that their chosen agent has loaded the tools, then test the workflow on a program they own and a narrow question they can check independently. A useful investigation should trace a complete example from input to result and distinguish observed behaviour from interpretation.
The report identifies REA 6.7.0 as the current release on October 19, 2026, but the supplied source does not describe a forthcoming release, roadmap or independent evaluation. Broader evidence about accuracy, safety and performance across different software types remains an open issue.
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Key Questions
What is Reverse Engineer Anything?
REA is an open-source toolkit that connects coding agents to software-analysis tools through MCP. It also includes a command-line utility and guidance for running investigations.
Does REA automatically recreate an application?
The report describes REA as a way to investigate a program’s behaviour, not as an automatic application-rebuilding system. Developers still need to interpret findings and implement and test their own software.
What did the QuickBooks case study report?
The article says a developer used REA to examine selected QuickBooks Desktop accounting rules and built Ledger Reborn. Its profit-and-loss statement, balance sheet and trial balance reportedly matched Intuit’s sample company figures to the cent; this account was not independently verified in the supplied source.
Does REA keep all analysis data on my computer?
REA runs analysis locally, according to the report, but findings are sent to the connected agent and may also go to its model provider. Data handling depends on the agent and provider’s policies.
Is it safe to inspect an unknown program?
The project warns that REA is not a sandbox. The report advises treating unknown programs as untrusted files because analysis tools run with the user’s permissions.
Source: ThorstenMeyerAI.com
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