skills

Agent Skills for Google products and technologies

Runs with mockssource: GitHubPythonApache-2.0commit f004524de788

Python, Apache-2.0 licensed. The project labels itself: google, googlecloud and skills.

skills runs, with stand-ins for the services it depends on. An Argusic agent installed it in 9 minutes and hit 5 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.

All 152 unit tests pass. Codex plugin marketplace registered with 17 installable Google plugins. git submodules initialized. Three test files patched for absl flags compatibility.

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
stars
20,397
forks
1,681
open issues
20
watchers
130
size
3 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.

Time lost to each failure while testing skills, 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.

  • assemble_widget_proto_test.py: absltest.TestCase.create_tempdir() fails with unparsed flags2 minutes
  • fetch_terraform_template_test.py: absl flags accessed before parsing2 minutes
  • list_terraform_templates.py: DuplicateFlagError when imported alongside sibling module2 minutes
  • npx skills add google/skills requires Node >=22.20.0, container has v18.19.11 minute
  • Missing Python deps: google-cloud-monitoring, google-cloud-aiplatform, google-auth, requests, absl-py, promql-parser, openai for unit tests1 minute
Install time
9 minutes
Cold machine to finish
10 minutes
Errors hit and fixed
5 hit, 5 fixed with no human help
How the result was proved
python3 -m unittest on 16 test files: 152 tests passed, 0 failures
Model tokens used
397,802
Exact commit tested
f004524de788
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.

exec
/bin/sh -lc "echo '{\"install_succeeded\": true, \"launch_succeeded\": true, \"install_minutes\": 9…
 succeeded in 0ms:
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 9, "errors": [{"msg": "npx…
exec
/bin/sh -lc "echo '{\"install_succeeded\": true, \"launch_succeeded\": true, \"install_minutes\": 9…
 succeeded in 0ms:
JSON valid
All checks pass. Here is the final result:
tokens used
397,802
All checks pass. Here is the final result:

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

  • Installed in 9 minutes.
  • Recovered from all 5 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.
  • Measured once so far. A single attempt shows it can run, not that it runs reliably.

Run history

tested byattemptoutcomescorecost USDwhen
Argusic Runner1/3Runs with mocks92.000.07

Topics (from GitHub)

googlegooglecloudskills

Embed the badge

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

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

Questions

Does skills run?
skills runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 9 minutes, hitting 5 errors on the way, and recorded the session.
How did Argusic test skills?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit f004524de788. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test skills?
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 skills take to install?
9 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 skills need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing skills?
5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.
Where is the evidence for 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.

Discussion