noob-visual-rca

Classify visual diff failures into root-cause categories from verification runs.

Updated Apr 4, 2026
One-click install
npx skills add https://github.com/ganeshgaxy/apps-for-testing --skill noob-visual-rca
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: noob-visual-rca
Source: https://github.com/ganeshgaxy/apps-for-testing/tree/main/.claude/skills/noob-visual-rca
Command: npx skills add https://github.com/ganeshgaxy/apps-for-testing --skill noob-visual-rca

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Classify visual diff failures from a completed verification run. Run after /noob-visual or /noob-visual-pool verification runs.

Core Features & Use Cases

  • Classify each failed visual comparison by examining Baseline, Current, and Diff images and assign a category such as visual_regression, intentional_change, flaky_render, env_issue, threshold_issue, or unknown.
  • Provide actionable guidance including suggested actions (fix_app, update_baseline, adjust_threshold, retry, fix_env, investigate) and an optional procedure to file a noob-tester issue for visual regressions.

Quick Start

Run the visual RCA workflow against the latest verification run to classify failures and optionally file issues for visual regressions.

Frequently Asked Questions about noob-visual-rca

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

FAQPage Schema
How do I classify visual diff failures to identify regressions?

Visual diff failures are classified by examining baseline, current, and diff images to map each failure to categories like visual_regression, intentional_change, flaky_render, env_issue, threshold_issue, or unknown. This streamlines debugging by pinpointing exact root causes.

What is the best way to triage visual regression test failures after a verification run?

The best way to triage visual regression test failures is running a post-verification root-cause analysis that compares baseline and current images, categorizing diffs and recommending remediation actions like fix_app, update_baseline, adjust_threshold, retry, or fix_env.

How do I know whether to update a baseline image or fix the app during bug triage?

During bug triage, the classification process determines if a visual diff is an intentional_change or visual_regression. An intentional_change suggests updating the baseline image, while a visual_regression recommends fixing the application code.

Can I automatically file issues for visual regressions detected during testing?

Yes, you can automatically file issues for visual regressions. The classification process provides an optional procedure to file a tester issue specifically for failures categorized as visual regressions, streamlining the bug reporting workflow.

Why do my visual tests fail with flaky renders or environment issues instead of actual regressions?

Visual tests often fail due to flaky_render or env_issue categories rather than real regressions. Root-cause analysis identifies these specific failure types and recommends actions like retrying the test or fixing the environment instead of modifying application code.

Does visual root-cause analysis work without a completed verification run?

No, visual root-cause analysis requires a completed verification run. It specifically applies to post-verification visual test outputs from the noob-visual and noob-visual-pool workflows to diagnose each failed comparison and guide remediation actions.