test

Name: test
Availability: InStock
Author: karimatayuta

Run pytest tests and generate concise failure summaries with patch hints.

Updated Feb 7, 2026

Search Tags:#testing #debugging #pytest #python #ci #test-analysis

Ready to run

npx skills add https://github.com/karimatayuta/graph-vector-rag --skill test-karimatayuta

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: test
Source: https://github.com/karimatayuta/graph-vector-rag/tree/main/.claude/skills/test
Command: npx skills add https://github.com/karimatayuta/graph-vector-rag --skill test-karimatayuta

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps developers run pytest tests, analyze failures quickly, and propose fixes to improve code quality and test reliability.

Core Features & Use Cases

Run pytest tests across unit, integration, and async test suites.
Analyze failure messages to produce concise summaries and suggested remediation steps.
Integrate with REPL or automation scripts to streamline debugging workflows in Python projects.

Quick Start

Run the test suite for your Python project, review the failing tests, and generate actionable fix recommendations.

Frequently Asked Questions about test

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze pytest failures and generate debugging summaries in Python?▼

To analyze pytest failures, run your test suite and the tool will identify failing tests, generating concise failure summaries to guide debugging and suggest actionable fixes. It evaluates unit, integration, and end-to-end suites to produce clear remediation steps.

Does pytest test analysis work with pytest-asyncio and end-to-end suites?▼

Yes, pytest test analysis works with pytest-asyncio across unit, integration, and end-to-end test suites. It diagnoses failures and provides guidance for flaky or invalid tests within your Python project's testing environment.

What is the best way to diagnose flaky or invalid pytest tests in Python?▼

The best way to diagnose flaky or invalid pytest tests is to run the test analyzer, which identifies failing tests and provides specific guidance for flaky or invalid tests, outputting concise failure summaries and patch hints to fix them.

What Python environment do I need to run pytest test analysis and generate patch hints?▼

You need Python 3.13+ and a valid test setup to run pytest test analysis and generate patch hints. Satisfying these environment prerequisites allows the tool to execute tests and provide actionable recommendations.

Why are my pytest tests failing and how do I get fix recommendations?▼

Your pytest tests may be failing due to code errors, flaky tests, or invalid test setups. Run the test analyzer to identify failing tests, generate concise failure summaries, and receive actionable recommendations and patch hints to resolve them.

Can I integrate pytest test debugging into REPL or automation scripts?▼

Yes, you can integrate pytest test debugging into REPL or automation scripts to streamline debugging workflows. This allows you to run tests, analyze failures, and generate fix recommendations directly within your Python project environment.