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test-analyzer

Analyzes test results and visual evidence to generate a consolidated pass/fail quality report.

1|Updated Mar 13, 2026
Search Tags:#testing#qa#jest#playwright#detox#visual-evidence
One-click install
npx skills add https://github.com/coreymaypray/sloth-skill-tree --skill test-analyzer-coreymaypray
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: test-analyzer
Source: https://github.com/coreymaypray/sloth-skill-tree/tree/main/plugins/maycrest-ops/skills/test-analyzer
Command: npx skills add https://github.com/coreymaypray/sloth-skill-tree --skill test-analyzer-coreymaypray

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

QA teams struggle to convert scattered test outputs, logs, and UI evidence into a single, trustworthy release verdict; this skill aggregates visual evidence and test results to deliver a clear quality assessment.

Core Features & Use Cases

  • Evidence collection: capture and log screenshots from mobile simulators, web previews, and CI logs.
  • Test result analysis: parse Jest and Detox outputs, identify failure patterns, and map coverage gaps.
  • Decision support: generate a data-backed go/no-go recommendation with traceable evidence across platforms.

Quick Start

Run the analyzer against a failing or flaky test suite to obtain a consolidated quality verdict.

Frequently Asked Questions about test-analyzer

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

FAQPage Schema
How do I convert scattered Jest and Detox test outputs into a single release verdict?▼

To convert scattered Jest and Detox outputs into a single release verdict, analyze test results and visual evidence together to generate a consolidated report with pass/fail analysis, coverage insights, and actionable go/no-go recommendations.

What is the best way to analyze Expo iOS and Android visual testing evidence?▼

The best way to analyze Expo iOS and Android visual testing evidence is to collect screenshots from mobile simulators and parse test outputs, mapping UI failures and coverage gaps to deliver a data-backed quality verdict.

How do I interpret CI logs and E2E results for a go/no-go decision?▼

To interpret CI logs and E2E results for a go/no-go decision, aggregate the test outputs and identify failure patterns across platforms to generate a trustworthy quality assessment with traceable evidence.

Can I use a single test analyzer for both Jest unit tests and Playwright E2E results?▼

Yes, you can use a single test analyzer for Jest unit tests and Playwright E2E results. It parses outputs across platforms, identifies failure patterns, and maps coverage gaps to produce a unified pass/fail analysis.

Why does my QA team struggle to map coverage gaps from scattered test outputs?▼

QA teams struggle to map coverage gaps from scattered test outputs because logs and UI evidence are fragmented. Aggregating visual evidence and test results resolves this by identifying failure patterns and generating a consolidated quality report.

Do I need to manually collect simulator screenshots before analyzing test results?▼

You do not need to manually collect simulator screenshots before analyzing test results. The analyzer captures and logs screenshots from mobile simulators, web previews, and CI logs automatically to support the quality verdict.

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