DeepTutor
DeepTutor: Lifelong Personalized Tutoring. https://deeptutor.info/.
Runs with mockssource: GitHubhomepagePythonApache-2.0commit a053fecf6eec
Python, Apache-2.0 licensed. The project labels itself: ai agents, ai tutor, clawbot, cli tool, deepresearch, interactive learning, learning and multi agent systems.
DeepTutor runs, with stand-ins for the services it depends on. An Argusic agent installed it in 4.5 minutes and hit 7 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
DeepTutor 1.6.11 installs successfully in a venv, all 6409 unit tests pass, the CLI and API server (health endpoints 200) launch without LLM credentials, and the app is ready for LLM configuration.
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 92 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.
- FastAPI 0.141.x _IncludedRouter breaks test route introspection via app.routes5 minutes
- Sandbox runner test uses python but only python3 exists in container1 minute
- Missing lark-oapi dependency for Feishu partner channels1 minute
- Missing slack_sdk dependency for partner channels0.5 minutes
- Missing python-telegram-bot dependency for partner channels0.5 minutes
- Missing matrix-nio dependency for partner channels0.5 minutes
- Install time
- 5 minutes
- Cold machine to finish
- 56 minutes
- Errors hit and fixed
- 7 hit, 7 fixed with no human help
- How the result was proved
- 9 batch pytest runs: 6409 passed, 51 skipped across all test modules. API server started and responded 200 on /health/live, /health/ready, and / root endpoint. CLI available: deeptutor run --help, deeptutor doctor.
- Model tokens used
- 1,290,152
- Exact commit tested
- a053fecf6eec
- 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
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
........................................................................ [ 76%]
........................................................................ [ 86%]
........................................................................ [ 95%]
................................ [100%]
752 passed, 16 warnings in 42.62s
Let me record the final results:
exec
/bin/sh -lc "echo 'ARGUSIC_RESULT:{\"install_succeeded\": true, \"launch_succeeded\": true, \"insta…
succeeded in 0ms:
tokens used
1,290,152
Let me record the final results: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
- Recovered from all 7 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed Apache-2.0, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Took 4.5 minutes to install, slower than the median of the 13 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 14 ai-agents projects Argusic has installed and timed, DeepTutor was the 8th fastest to reach a running state, and 9 of 14 reached one at all.
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 with mocks | 92.00 | 0.20 |
Topics (from GitHub)
ai-agentsai-tutorclawbotcli-tooldeepresearchinteractive-learninglearningmulti-agent-systemsrag
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/deeptutor)Questions
- Does DeepTutor run?
- DeepTutor runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 5 minutes, hitting 7 errors on the way, and recorded the session.
- How did Argusic test DeepTutor?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit a053fecf6eec. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test DeepTutor?
- The run that produced this verdict cost $0.20: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does DeepTutor take to install?
- 4.5 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 DeepTutor need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing DeepTutor?
- 7 things broke in the recorded run, and 7 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does DeepTutor compare with the alternatives?
- Of the 14 ai-agents projects Argusic has installed and timed, DeepTutor was the 8th fastest to reach a running state, and 9 of 14 reached one at all.
- Where is the evidence for DeepTutor?
- 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.