github-readme-stats

:zap: Dynamically generated stats for your github readmes

Runssource: GitHubhomepageJavaScriptMITcommit 54a7985aeefd

JavaScript, MIT licensed. The project labels itself: dynamic, profile readme, readme generator, readme stats and serverless.

github-readme-stats runs. An Argusic agent installed it in 0.2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

npm install completed, 27 test suites (242 tests) pass, and the Express server serves SVG cards (stats, top-langs, pin, wakatime, gist) on port 9000 responding HTTP 200.

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 97.3 of 100 (the mean of this project's run scores).

At a glance

verdict
Runs
Argusic Score
97.3 / 100
cost of the verifying run
$0.01 (measured)
recorded runs
3
last tested
stars
79,821
forks
37,959
open issues
295
watchers
314
size
8 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
under a minute
Cold machine to finish
4 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
npm test: 27 suites, 242 tests passed. Express server: curl /api?username=anuraghazra -> 200 SVG, /api/top-langs?username=anuraghazra -> 200 SVG, /api/pin?username=anuraghazra&repo=github-readme-stats -> 200 SVG, /api/wakatime?username=anuraghazra -> 200 SVG, /api/gist?id=somegistid -> 200 SVG
Model tokens used
37,031
Exact commit tested
54a7985aeefd
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 3, run , the attempt that decided the verdict above. 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.

37,031
Here's my final analysis.
All went smoothly — npm install succeeded (with engine warnings for Node v18 vs the required v22), …
| Metric | Value |
|--------|-------|
| **install_succeeded** | true |
| **launch_succeeded** | true |
| **install_minutes** | 0.2 |
| **errors** | none |
| **test_depth** | tier1_real |
| **verified_how** | Test suite: 27 suites, 242 passed. Express server: `curl /api?username=anuragh…
| **final_state** | npm install completed, 27 test suites (242 tests) pass, and the Express server …

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 0.2 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 MIT, as reported by its host.
  • Measured 3 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 0.2 minutes after the clone.
  • Following its own README: the documented path worked with nothing to fix.

Run history

tested byattemptoutcomescorecost USDwhen
Argusic Runner3/3Runs100.000.01
Argusic Runner2/3Runs100.000.01
Argusic Runner1/3Runs with mocks92.000.04

Topics (from GitHub)

dynamicprofile-readmereadme-generatorreadme-statsserverless

Embed the badge

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

[![Tested by Argusic](https://argusic.com/badge/github-readme-stats.svg)](https://argusic.com/subject/github-readme-stats)

Questions

Does github-readme-stats run?
Yes. github-readme-stats runs. Argusic installed and launched it on a clean machine in 0 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test github-readme-stats?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit 54a7985aeefd. 3 attempts are recorded, and the full method is on the methodology page.
What did it cost to test github-readme-stats?
The run that produced this verdict cost $0.01: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does github-readme-stats take to install?
0.2 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 github-readme-stats need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing github-readme-stats?
Nothing did, in the recorded run: zero errors between clone and running.
Where is the evidence for github-readme-stats?
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.

Discussion