nxnative
Switch games running natively on iPhone, iPad and Mac: an NSP folder becomes an unsigned IPA (NSO rewriter, Horizon HLE host, NVN→Metal)
Runssource: GitHubPythonMITcommit ac9598ad83e2
Python, MIT licensed.
nxnative runs. An Argusic agent installed it in 12 minutes and hit 5 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
All Linux-compatible Python tool tests pass: NSO/NRO loader, NSP packing, RomFS image builder, shader splitter, rewriter, docs/lint/env tools all verified working on Ubuntu 24.04 with Python 3.12
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 90 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page. Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- Missing Python deps: lz4, capstone, fonttools, zstd, backports.zstd3 minutes
- Pip could not install into system Python (externally-managed-environment)1 minute
- gcc-13 -Wmisleading-indentation error on one-liner C in test_romfs_image.py1 minute
- Pre-existing flaky test test_romfs_image.py::test_reuse_rebuilds_changed_added_removed_and_renamed_files (ext4 ctime resolution)
- test_spirv_cross_pin, test_nsp_mac_app, test_own_compilers, test_regress need macOS/Xcode
- Install time
- 12 minutes
- Cold machine to finish
- 6 minutes
- Errors hit and fixed
- 5 hit, 5 fixed with no human help
- How the result was proved
- python3 -m pytest dm/tools/tests passed 449 tests (20 skipped, 2 xfailed, 338 subtests passed) after fixing one gcc-13 indentation bug and installing 5 pip dependencies
- Model tokens used
- 85,832
- Exact commit tested
- ac9598ad83e2
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
Let me check whether the test suite uses real test data or mocks. exec /bin/sh -lc 'cd /work/repo && find dm/tools/tests -name "*.nso" -o -name "*.nro" -o -name "*.nsp" -… succeeded in 0ms: exec /bin/sh -lc 'cd /work/repo && . /tmp/venv/bin/activate && python3 -m pytest dm/tools/tests/ -q --tb… succeeded in 5121ms: 443 passed, 19 skipped, 44 deselected, 2 xfailed, 326 subtests passed in 4.93s Now I have all the data I need. Let me compile the final report. tokens used 85,832 Now I have all the data I need. Let me compile the final report.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Recovered from all 5 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- Took 12 minutes to install, slower than the median of the 43 comparable projects Argusic has measured.
Of the 44 Python projects Argusic has installed and timed, nxnative was the 38th fastest to reach a running state, and 23 of 44 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Runs | 100.00 | 0.18 | |
| Argusic Runner | 1/3 | Unverified | 80.00 | 0.42 |
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/nxnative)Questions
- Does nxnative run?
- Yes. nxnative runs. Argusic installed and launched it on a clean machine in 12 minutes, hitting 5 errors on the way, and recorded the session.
- How did Argusic test nxnative?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit ac9598ad83e2. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test nxnative?
- The run that produced this verdict cost $0.18: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does nxnative take to install?
- 12 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does nxnative need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing nxnative?
- 5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does nxnative compare with the alternatives?
- Of the 44 Python projects Argusic has installed and timed, nxnative was the 38th fastest to reach a running state, and 23 of 44 reached one at all.
- Where is the evidence for nxnative?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.