auto-editor
Effort free video editing!
Runssource: GitHubhomepageNimUnlicensecommit eb41d26177de
Nim, Unlicense licensed. The project labels itself: audio, audio editing, audio processing, automatic, nim, video, video editing and video processing.
auto-editor runs. An Argusic agent installed it in 36.6 minutes and hit 6 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
auto-editor builds and runs: processes MP4 files with audio-level-based silence detection and h264+aac re-encoding, producing valid output with zero decode errors
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 100 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . 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.
- Encoder not found: h264 at runtime; built FFmpeg without h264 encoder12 minutes
- System FFmpeg 6.1 headers missing AVCodecConfig enum needed by FFmpeg 9.x API in Nim code8 minutes
- meson/ninja not installed; makeff task failed on pip install due to externally-managed-environment4 minutes
- FFmpeg dev headers not installed - libavutil/rational.h missing2 minutes
- Linker errors: -lmp3lame -lopus -lx264 -ldav1d -lz -lasound not found2 minutes
- Undefined x264 symbols at link after rebuild1 minute
- Install time
- 37 minutes
- Cold machine to finish
- 40 minutes
- Errors hit and fixed
- 6 hit, 6 fixed with no human help
- How the result was proved
- /work/repo/auto-editor resources/testsrc.mp4 --output /tmp/test_out.mp4 exited 0, ffprobe confirmed valid h264+aac streams; auto-editor /work/repo/example.mp4 --output /tmp/example_edited.mp4 exited 0, ffmpeg -v error -i /tmp/example_edited.mp4 -f null - returned no errors
- Model tokens used
- 1,392,042
- Exact commit tested
- eb41d26177de
- 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
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 1, run . The verdict above comes from a different attempt, so read this as one session and not as the current result. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
/bin/sh -lc 'date +%s' in /work/repo
succeeded in 0ms:
1790279735
Now let me produce the final report. The start was around 19:16 based on timestamps, and it's curre…
exec
/bin/sh -lc "python3 -c \"print(f'{(1790279735 - 1790277537)/60:.1f} minutes')\"" in /work/repo
succeeded in 0ms:
36.6 minutes
All clear. Here is the final report.
tokens used
1,392,042
All clear. Here is 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 6 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 Unlicense, as reported by its host.
- Measured 3 times, so the result is not a one-off.
What did not, or is not known
- Took 36.6 minutes to install, slower than the median of the 17 comparable projects Argusic has measured.
Of the 18 audio projects Argusic has installed and timed, auto-editor was the 18th fastest to reach a running state, and 15 of 18 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.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
Topics (from GitHub)
audioaudio-editingaudio-processingautomaticnimvideovideo-editingvideo-processing
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/auto-editor)Questions
- Does auto-editor run?
- Yes. auto-editor runs. Argusic installed and launched it on a clean machine in 37 minutes, hitting 6 errors on the way, and recorded the session.
- How did Argusic test auto-editor?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit eb41d26177de. 3 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test auto-editor?
- The run that produced this verdict cost $0.44: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does auto-editor take to install?
- 36.6 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 auto-editor need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing auto-editor?
- 6 things broke in the recorded run, and 6 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does auto-editor compare with the alternatives?
- Of the 18 audio projects Argusic has installed and timed, auto-editor was the 18th fastest to reach a running state, and 15 of 18 reached one at all.
- Where is the evidence for auto-editor?
- All 3 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.