This was made collaboratively by me directing coding agents at the binary, using Ghidra MCP extensively, diassembly and also dynamic analysis with an emulator. I don't have a writeup of the process but it was definitely not fully automatable (I wish though). I might prepare a blog post with transcripts and session history and things I learned along the way.
Broad takeaways:
- Ghidra MCP is not a silver bullet. Lots of opportunities for mis-decoding especially on older instruction sets (e.g. conflating code + data), which requires user input to flag data layout/structs.
- Agents still need a lot of user direction otherwise the RE production is just kind of a random walk. With Z80 it's decent at reading code but I expect that it has much worse performance than reading x86 or ARM for instance. The TI-84+ has a bunch of hardware quirks as well.
- GPT 5.5 is better than Opus 4.8 at RE. Opus 4.8 loves plausible-sounding RE'd logic without any checking. The gold standard is actually dynamically executing the binary and comparing the logic against the prose.
- Maintaining consistency in style and prose is a PITA across the wiki. Hard to reconcile prose <-> code. Can be somewhat mitigated by agent loops.
Was also in discussions with people in the TI calculator programming space who helped provide guidance as well. We previously did not have a catalogue of every subsystem in TI-OS yet alone most subroutines in the OS.
It's highly likely that the original implementation language was assembly. The code is very idiomatic.
Regarding source build, I think reverse engineering it to the point where you can reconstruct the source is possibly legally problematic, so I don't plan to do this, but maybe for certain subsystems like MathPrint (equation display) which was especially fun to RE. I have a PR up for it and it will be live at
The plans are heavily subsidized by the AI companies so I didn't end up needing to do API usage or buy another subscription. I have ChatGPT Pro and Claude Code Max.
Broad takeaways:
- Ghidra MCP is not a silver bullet. Lots of opportunities for mis-decoding especially on older instruction sets (e.g. conflating code + data), which requires user input to flag data layout/structs.
- Agents still need a lot of user direction otherwise the RE production is just kind of a random walk. With Z80 it's decent at reading code but I expect that it has much worse performance than reading x86 or ARM for instance. The TI-84+ has a bunch of hardware quirks as well.
- GPT 5.5 is better than Opus 4.8 at RE. Opus 4.8 loves plausible-sounding RE'd logic without any checking. The gold standard is actually dynamically executing the binary and comparing the logic against the prose.
- Maintaining consistency in style and prose is a PITA across the wiki. Hard to reconcile prose <-> code. Can be somewhat mitigated by agent loops.
Was also in discussions with people in the TI calculator programming space who helped provide guidance as well. We previously did not have a catalogue of every subsystem in TI-OS yet alone most subroutines in the OS.
Regarding source build, I think reverse engineering it to the point where you can reconstruct the source is possibly legally problematic, so I don't plan to do this, but maybe for certain subsystems like MathPrint (equation display) which was especially fun to RE. I have a PR up for it and it will be live at
https://siraben.github.io/ti84p-re/mathprint
> The big picture
> The structural reverse-engineering is comprehensive (every subsystem mapped, both cross-page mechanisms resolved ...
> Confidence summary / open items
Probably an LLM wrote the docs.
> (the GhidraMCP plugin reconnects for interactive work)
Probably LLM+Ghidra for the actual RevEng. Ultimately does it matter if the end product is works though