Does khazix-skills run?

Yes. khazix-skills runs. Argusic installed and launched it on a clean machine in 5 minutes, hitting 0 errors on the way, and recorded the session.

How did Argusic test khazix-skills?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4f2db0980273. One attempt is recorded, and the full method is on the methodology page.

What did it cost to test khazix-skills?

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 khazix-skills take to install?

5.2 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 khazix-skills need a GPU?

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

What goes wrong when installing khazix-skills?

Nothing did, in the recorded run: zero errors between clone and running.

Where is the evidence for khazix-skills?

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.

khazix-skills

数字生命卡兹克开源的 AI Skills 合集 | Agent Skills: leader（帮你定义目标）, neat-freak 洁癖, hv-analysis, khazix-writer & more, Claude Code, Codex & 40+ agents

Runssource: GitHubPythonMITcommit 4f2db0980273

Python, MIT licensed. The project labels itself: agent skills, ai agents, claude, claude code, codex, developer tools, llm and skills.

khazix-skills runs. An Argusic agent installed it in 5.2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

aihot skill installed and its live API returns real AI news (HTTP 200 with real items); neat-freak all 11 structural regressions and 21 trigger evals pass; hv-analysis md_to_pdf.py generates valid PDFs via WeasyPrint; storage-analyzer build_report.py and server.py produce and serve disk-usage reports; scan.py correctly rejects Linux per documented platform limitation; all scripts require zero third-party API keys
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: 2026-09-25
stars: 20,937
forks: 2,216
open issues: 49
watchers: 118
size: 0 MB
created: 2026-04-06
last push: 2026-09-25

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.

Install time: 5 minutes
Cold machine to finish: 5 minutes
Errors hit and fixed: 0 hit, 0 fixed with no human help
How the result was proved: aihot install.sh --target codex installed v1.7.2 to ~/.agents/skills/aihot; AIHOT API GET /api/v1/items returned HTTP 200 with 3 real news items; neat-freak validate.py exited 0: description=802 chars, body=210 lines, behavior_evals=11, trigger_evals=21, intent_positives=8; hv-analysis md_to_pdf.py generated 7.9KB valid PDF (9 objects, xref, %%EOF) via WeasyPrint 70.0; storage-analyzer build_report.py + test JSON produced 27KB HTML report; server.py module test: GET / returned 200 with rendered HTML, POST /action with valid token returned 200, bad token rejected 403, unknown path returned 404; audit-inventory.sh ran OK on repo root
Model tokens used: 166,247
Exact commit tested: 4f2db0980273
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.

        'scan.py correctly rejects Linux per documented platform limitation; '
        'all scripts require zero third-party API keys'
    )
}
# validate JSON output
j = json.dumps(result, ensure_ascii=False)
print(j)
\" 2>&1" in /work/repo
 succeeded in 0ms:
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 5.2, "errors": [], "test_d…
tokens used
166,247

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.
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.

What did not, or is not known

Took 5.2 minutes to install, slower than the median of the 11 comparable projects Argusic has measured.
Measured once so far. A single attempt shows it can run, not that it runs reliably.

Of the 12 agent-skills projects Argusic has installed and timed, khazix-skills was the 10th fastest to reach a running state, and 10 of 12 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.
A quick evaluation: it was running 5.2 minutes after the clone.
Following its own README: the documented path worked with nothing to fix.

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	0.03	2026-09-25 22:22 UTC

Topics (from GitHub)

agent-skills ai-agents claude claude-code codex developer-tools llm skills vibe-coding

Embed the badge

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

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

Questions

Does khazix-skills run?: Yes. khazix-skills runs. Argusic installed and launched it on a clean machine in 5 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test khazix-skills?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4f2db0980273. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test khazix-skills?: 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 khazix-skills take to install?: 5.2 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 khazix-skills need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing khazix-skills?: Nothing did, in the recorded run: zero errors between clone and running.
How does khazix-skills compare with the alternatives?: Of the 12 agent-skills projects Argusic has installed and timed, khazix-skills was the 10th fastest to reach a running state, and 10 of 12 reached one at all.
Where is the evidence for khazix-skills?: 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.