Yes. leon runs. Argusic installed and launched it on a clean machine in 12 minutes, hitting 3 errors on the way, and recorded the session.

How did Argusic test leon?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit a8f2052fb6d9. One attempt is recorded, and the full method is on the methodology page.

What did it cost to test leon?

The run that produced this verdict cost $0.04: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.

How long does leon 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 leon need a GPU?

Not to start. Argusic reached a running state on a machine with no GPU.

What goes wrong when installing leon?

3 things broke in the recorded run, and 3 were fixed without human help. Each one, and the time it cost, is listed on this page.

Where is the evidence for leon?

The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.

leon

🧠 Leon is your open-source personal assistant.

Runssource: GitHub homepageTypeScriptMITcommit a8f2052fb6d9

TypeScript, MIT licensed. The project labels itself: ai, ai agent, ai assistant, artificial intelligence, assistant, automation, bot and chatbot.

leon runs. An Argusic agent installed it in 12 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.

Leon 1.0.0-beta.10+dev is installed with managed Node.js v24.21.0, pnpm 12.4.1, Python 3.11.9, uv 0.10.12, cmake 4.3.2, and ninja 1.13.2. The HTTP server boots on port 5366 and responds 200. All 371 unit tests pass. The web app, LLM providers, voice services, and the PaddleOCR model are not configured and were not exercised, which is the expected default state.
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

verdict: Runs
Argusic Score: 100 / 100
cost of the verifying run: $0.04 (measured)
recorded runs: 1
last tested: 2026-09-26
stars: 17,550
forks: 1,473
open issues: 113
watchers: 276
size: 35 MB
created: 2019-02-10
last push: 2026-09-26

Subject data from GitHub, linked at the top of this page, refreshed 2026-09-26. 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.

Time lost to each failure while testing leon, drawn from the recorded run — Every bar is a failure the agent recorded, with the time it cost. Drawn from this run, not from anywhere else.

What went wrong, in the agent's own words

The agent's own words, worst first, never rewritten into advice.

System Node.js version was v18.19.1, but Leon requires Node.js >=24.0.0. pnpm refused to install.4 minutes
Setup failed at setupNinja: 'spawnSync unzip ENOENT' -- unzip is not in the container.3 minutes
2 integration tests failed: document-reader.spec.ts - Missing managed OCR resource: PaddleOCR-v6-small-det/inference.onnx

Install time: 12 minutes
Cold machine to finish: 6 minutes
Errors hit and fixed: 3 hit, 3 fixed with no human help
How the result was proved: pnpm test:unit exited 0, 371 passed, 40 files; curl -s -o /dev/null -w '%{http_code}' http://localhost:5366 returned 200; pnpm run check exited 1 only due to expected 'No LLM configured' warning
Model tokens used: 194,456
Exact commit tested: a8f2052fb6d9
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.

Unit tests: 371 passed, 40 files
Integration tests: 28 passed, 2 failed (OCR - missing PaddleOCR model, tool-level dep)
Server: GET / returned 200
Node: v24.21.0 (managed), pnpm: 12.4.1, Python: 3.11.9
```json
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 12, "errors": [{"msg": "Sy…
```
tokens used
194,456
```json
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 12, "errors": [{"msg": "Sy…
```

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 3 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.

What did not, or is not known

Took 12 minutes to install, slower than the median of the 40 comparable projects Argusic has measured.
Measured once so far. A single attempt shows it can run, not that it runs reliably.

Of the 41 ai projects Argusic has installed and timed, leon was the 34th fastest to reach a running state, and 34 of 41 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

tested by	attempt	outcome	score	cost USD	when
Argusic Runner	1/3	Runs	100.00	0.04	2026-09-26 04:22 UTC

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/leon.svg)](https://argusic.com/subject/leon)

Questions

Does leon run?: Yes. leon runs. Argusic installed and launched it on a clean machine in 12 minutes, hitting 3 errors on the way, and recorded the session.
How did Argusic test leon?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit a8f2052fb6d9. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test leon?: The run that produced this verdict cost $0.04: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does leon 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 leon need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing leon?: 3 things broke in the recorded run, and 3 were fixed without human help. Each one, and the time it cost, is listed on this page.
How does leon compare with the alternatives?: Of the 41 ai projects Argusic has installed and timed, leon was the 34th fastest to reach a running state, and 34 of 41 reached one at all.
Where is the evidence for leon?: The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.