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17 changes: 17 additions & 0 deletions .github/workflows/ovoscope.yml
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name: Skill End-to-End Tests (ovoscope)

on:
pull_request:
branches: [dev, master, main]
workflow_dispatch:

jobs:
ovoscope:
uses: OpenVoiceOS/gh-automations/.github/workflows/ovoscope.yml@dev
secrets: inherit
with:
python_version: '3.11'
install_extras: 'test'
test_path: 'test/end2end/'
system_deps: 'swig'
require_padatious: true
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53 changes: 53 additions & 0 deletions ovos_skill_diagnostics.egg-info/PKG-INFO
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Metadata-Version: 2.4
Name: ovos-skill-diagnostics
Version: 0.0.11a1
Summary: OVOS diagnostics skill
Home-page: https://github.com/OpenVoiceOS/ovos-skill-diagnostics
Author: OpenVoiceOS
Author-email: jarbasai@mailfence.com
License: Apache-2.0
Keywords: ovos skill plugin
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ovos_workshop>=0.0.12
Requires-Dist: ovos-lang-parser
Requires-Dist: psutil
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

# <img src='https://raw.githack.com/FortAwesome/Font-Awesome/master/svgs/solid/info-circle.svg' card_color='#22a7f0' width='50' height='50' style='vertical-align:bottom'/> System Diagnostics
Retrieve system information such as CPU, memory, and language settings.

## About
The **System Diagnostics Skill** provides various system metrics, including kernel version, CPU and memory usage, GPU availability, and language settings. Users can query these details via voice commands.

## Examples
* "What is your kernel version?"
* "Do you have a GPU?"
* "What is your CPU usage?"
* "How much memory are you using?"
* "What language are you using?"

## Category
**System**

## Tags
#system
#diagnostics
#hardware
#performance
#language

## Credits

<img src="img.png" width="128"/>

> This skill was funded by the Ministerio para la Transformación Digital y de la Función Pública and Plan de Recuperación, Transformación y Resiliencia - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337
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