qinglong

支持 Python3、JavaScript、Shell、Typescript 的定时任务管理平台(Timed task management platform supporting Python3, JavaScript, Shell, Typescript)

Runssource: GitHubhomepageTypeScriptApache-2.0commit a67d44cde54f

TypeScript, Apache-2.0 licensed. The project labels itself: crontab, docker, javascript, python, shell, task manager and typescript.

qinglong runs. An Argusic agent installed it in 2.1 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

Dependencies installed, TypeScript back-end compiles, all 232 unit tests pass, the server starts on ports 5700 (HTTP) and 5500 (gRPC), and the API responds correctly

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
$0.03 (measured)
recorded runs
1
last tested
stars
19,904
forks
3,222
open issues
95
watchers
140
size
18 MB
created
last push

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.

Install time
2 minutes
Cold machine to finish
7 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
pnpm install, tsc build, npm test (232 passed, 0 failed), and curl confirmed HTTP 200 on /api/health and /api/system
Model tokens used
175,564
Exact commit tested
a67d44cde54f
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.

175,564
Everything is verified and working. Here's my summary:
**Installation**: `pnpm install` completed successfully — 1716 packages installed, SQLite binary do…
**Build**: `tsc -p back/tsconfig.json` compiled the back-end TypeScript to `static/build/` with zer…
**Tests**:
- 217 back-end tests passed, 0 failed (53.8s)
- 15 front-end tests passed, 0 failed (1.75s)
- **Total: 232 tests passed, 0 failures**
**App launch**: The server starts a gRPC worker on port 5500 and an HTTP worker on port 5700. The d…
- `GET /api/health` → `{"code":200,"data":{"status":"ok","services":{"http":true,"grpc":true}}}`
- `GET /api/system` → `{"code":200,"data":{"isInitialized":false,"version":"2.22.0",...}}`
- `POST /api/user/login` → `{"code":450,"message":"请先初始化"}` (expected — fresh install requires init…

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 2.1 minutes.
  • Nothing broke on the way: zero errors between clone and running.
  • Ran without a GPU, so it does not need one to start.
  • Licensed Apache-2.0, as reported by its host.

What did not, or is not known

  • Measured once so far. A single attempt shows it can run, not that it runs reliably.

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 2.1 minutes after the clone.
  • Following its own README: the documented path worked with nothing to fix.

Run history

tested byattemptoutcomescorecost USDwhen
Argusic Runner1/3Runs100.000.03

Topics (from GitHub)

crontabdockerjavascriptpythonshelltask-managertypescript

Embed the badge

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

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

Questions

Does qinglong run?
Yes. qinglong runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test qinglong?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit a67d44cde54f. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test qinglong?
The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does qinglong take to install?
2.1 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 qinglong need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing qinglong?
Nothing did, in the recorded run: zero errors between clone and running.
Where is the evidence for qinglong?
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.

Discussion