Does SoftwareCopyright-Skill run?

SoftwareCopyright-Skill runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 10 minutes, hitting 1 error on the way, and recorded the session.

How did Argusic test SoftwareCopyright-Skill?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit 947d5963194b. One attempt is recorded, and the full method is on the methodology page.

What did it cost to test SoftwareCopyright-Skill?

The run that produced this verdict cost $0.07: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.

How long does SoftwareCopyright-Skill take to install?

10 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 SoftwareCopyright-Skill need a GPU?

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

What goes wrong when installing SoftwareCopyright-Skill?

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 SoftwareCopyright-Skill?

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.

SoftwareCopyright-Skill

中国软件著作权申请材料生成器 Skills，本 Skills 通过阅读本地项目，自动生成全套 .docx 软著申请材料，全开源，无须再付费购买任何软著申请服务

Runs with mockssource: GitHubPythonMITcommit 947d5963194b

Python, MIT licensed.

SoftwareCopyright-Skill runs, with stand-ins for the services it depends on. An Argusic agent installed it in 10 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 12 Python scripts compile and pass static analysis; 32 unit tests pass; demo DOCX output files are valid OpenXML; scripts can analyze projects and extract code materials; OfficeCLI dependency is correctly detected as unavailable for final DOCX generation
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

verdict: Runs with mocks
Argusic Score: 92 / 100
cost of the verifying run: $0.07 (measured)
recorded runs: 1
last tested: 2026-09-30
stars: 5,687
forks: 0
open issues: 0
watchers: 0
created: -
last push: -

Subject data from GitHub, linked at the top of this page. 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.

Time lost to each failure while testing SoftwareCopyright-Skill, drawn from the recorded run — Every bar is a failure the agent recorded, with the time it cost. Drawn from this run, not from anywhere else.

What went wrong, in the agent's own words

The agent's own words, worst first, never rewritten into advice.

test_playwright_cli_uses_global_prefix_without_restart: test created .cmd file (Windows) on Linux; npm_global_candidates returns bin/playwright-cli on POSIX, causing test failure3 minutes

Install time: 10 minutes
Cold machine to finish: 11 minutes
Errors hit and fixed: 1 hit, 1 fixed with no human help
How the result was proved: python3 -m unittest discover -s software-copyright-materials/tests -q exited 0: 32 tests passed; python3 -m compileall -q software-copyright-materials/scripts exited 0; all 12 scripts import without errors; demo DOCX files validated as valid OpenXML via zipfile; analyze_project, propose_code_selection, and extract_code_material scripts ran successfully against test project
Model tokens used: 124,452
Exact commit tested: 947d5963194b
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.

      "msg": "test_playwright_cli_uses_global_prefix_without_restart: Test created .cmd file (Windo…
      "fix": "Changed test to create bin/playwright-cli with shebang instead of playwright-cli.cmd …
      "minutes": 3
    }
  ],
  "test_depth": "tier2_mock",
  "notes": "Argusic Agent skill for generating Chinese software copyright materials. No Python depe…
  "verified_how": "python3 -m unittest discover -s software-copyright-materials/tests -q exited 0: …
  "final_state": "All 12 Python scripts compile and pass static analysis; 32 unit tests pass; demo …
}
tokens used
124,452

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 1 error without a human stepping in, which says the failures are documented well enough to solve.
Licensed MIT, 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 10 minutes to install, slower than the median of the 22 comparable projects Argusic has measured.
Measured once so far. A single attempt shows it can run, not that it runs reliably.

Of the 23 Python projects Argusic has installed and timed, SoftwareCopyright-Skill was the 19th fastest to reach a running state, and 12 of 23 reached one at all.

Run history

tested by	attempt	outcome	score	cost USD	when
Argusic Runner	1/3	Runs with mocks	92.00	0.07	2026-09-30 07:41 UTC

Embed the badge

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

[![Tested by Argusic](https://argusic.com/badge/SoftwareCopyright-Skill.svg)](https://argusic.com/subject/softwarecopyright-skill)

Questions

Does SoftwareCopyright-Skill run?: SoftwareCopyright-Skill runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 10 minutes, hitting 1 error on the way, and recorded the session.
How did Argusic test SoftwareCopyright-Skill?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit 947d5963194b. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test SoftwareCopyright-Skill?: The run that produced this verdict cost $0.07: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does SoftwareCopyright-Skill take to install?: 10 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 SoftwareCopyright-Skill need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing SoftwareCopyright-Skill?: 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.
How does SoftwareCopyright-Skill compare with the alternatives?: Of the 23 Python projects Argusic has installed and timed, SoftwareCopyright-Skill was the 19th fastest to reach a running state, and 12 of 23 reached one at all.
Where is the evidence for SoftwareCopyright-Skill?: 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.