wizarr
Wizarr is an advanced user invitation and management system for Jellyfin, Plex, Emby etc.
Runssource: GitHubhomepagePythonMITcommit 7bafd55c7c3a
Python, MIT licensed. The project labels itself: emby, inviter, jellyfin, management, plex, selfhosted and user.
wizarr runs. An Argusic agent installed it in 4 minutes and hit 1 error and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
All 610 unit/integration tests pass, the Flask app starts and serves HTTP on port 5000 with Swagger API docs at /api/docs/, and database migrations apply cleanly from scratch.
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.
- Stale /tmp/wizarr_test.db SQLite WAL/journal artifacts from prior run caused 'disk I/O error' and 'table notification already exists' in test_session_grouping.py and test_invitation_unit.py2 minutes
- Install time
- 4 minutes
- Cold machine to finish
- 11 minutes
- Errors hit and fixed
- 1 hit, 1 fixed with no human help
- How the result was proved
- uv run pytest tests/ --ignore=tests/e2e exited 0, 610 passed, 1 skipped; curl -s -o /dev/null -w %{http_code} localhost:5000 returned 302; localhost:5000/api/docs/ returned 200; localhost:5000/api/swagger.json returned 200
- Model tokens used
- 102,270
- Exact commit tested
- 7bafd55c7c3a
- 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.
- `GET /api/swagger.json` → `200` (OpenAPI spec) No third-party keys or mocks were needed to verify the base application. tokens used 102,270 All verified. Here's the summary: **Install**: `uv sync` installed all 72 production dependencies and 42 dev dependencies successfull… **Test results**: 610 passed, 1 skipped, 0 failed on a clean test database. The `test_session_group… **App launch**: HTTP server started and responded: - `GET /` → `302` (redirect to onboarding/setup, expected for fresh install) - `GET /api/docs/` → `200` (Swagger UI) - `GET /api/swagger.json` → `200` (OpenAPI spec) No third-party keys or mocks were needed to verify the base application.
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.
- Installed in 4 minutes.
- Recovered from all 1 error 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 it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- A quick evaluation: it was running 4 minutes after the clone.
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)
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/wizarr)Questions
- Does wizarr run?
- Yes. wizarr runs. Argusic installed and launched it on a clean machine in 4 minutes, hitting 1 error on the way, and recorded the session.
- How did Argusic test wizarr?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 7bafd55c7c3a. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test wizarr?
- 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 wizarr take to install?
- 4 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 wizarr need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing wizarr?
- 1 thing broke in the recorded run, and 1 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for wizarr?
- 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.