Quality Metrics

Name: Quality Metrics
Author: proffesor-for-testing

Checked

proffesor-for-testing·vlatest·devops·MIT

This skill analyzes text for readability, grammar, and style, providing valuable insights to improve clarity and overall writing quality.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add proffesor-for-testing/agentic-qe --skill quality-metrics -a claude-code

Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

proffesor-for-testing

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned 11 Oct 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned proffesor-for-testing/agentic-qe at 124d8c735e.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: 124d8c735e
Manifest: assets/skills/quality-metrics/SKILL.md
Scanned: 8 files, 2,180 lines
Copies in repo: 2 — all of them scanned

This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.

What each check looks for →

About this skill

The quality-metrics skill enables AI agents to discover, install, and manage specific performance indicators for software testing workflows. It provides a structured way to define how an agent evaluates the success or failure of its execution tasks based on quantitative data.

When to use it

Establishing objective benchmarks for automated regression test suites.
Monitoring real-time pass/fail rates during continuous integration pipelines.
Generating reports on code coverage and defect density after a testing run.
Comparing performance metrics across different versions of an application.

Key capabilities

Discovery and retrieval of available quality metric definitions.
Installation of specific metric configurations for agent use cases.
Integration with agentic QA frameworks to automate data collection.

Example prompts

"Install the standard regression test coverage metrics for this project."
"Configure the agent to track defect density and report it after every build."
"What quality metrics are available for evaluating API response times?"

Tips & gotchas

Ensure your testing framework supports the specific metric types you intend to install, as compatibility varies by tool. Always verify that the installed metrics align with your organization's specific definition of "quality" before automating reporting.