How does this differ from standard unit testing?

While functional testing asks 'Does it work?', this skill asks 'Is this what we asked for?', focusing on compliance with specifications and visual accuracy.

Can I customize the severity levels of found issues?

Yes, the skill defines a classification system (blocker, tech_debt, skippable) that allows you to decide which issues require immediate fixes and which can be documented.

What is the benefit of the resolution loop?

It creates an automated cycle where blockers are identified, patched, and re-reviewed up to a defined limit (typically 3 attempts), reducing manual back-and-forth during the development phase.

Does this skill actually take screenshots?

The skill provides the design and structure for screenshot capture points; it is typically used in conjunction with browser automation tools to generate the actual visual proof.

Review Workflow Design

Name: Review Workflow Design
Author: melodic-software

bymelodic-software

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Security & Testing

Automates spec-based implementation reviews with visual verification and structured issue classification.

About

The Review Workflow Design skill enables teams to move beyond basic functional testing by establishing a formal process to verify that implementations strictly adhere to initial specifications. It provides a structured framework for identifying specification locations, capturing visual screenshots at critical path points, and classifying issues into blockers or technical debt. By integrating an auto-resolution loop, this skill ensures that discrepancies between requirements and the final build are caught and remediated systematically, providing stakeholders with tangible proof of delivery.

Key Features

Visual verification via multi-stage screenshot capture points
Comprehensive review artifact generation with visual proof
1 GitHub stars
Automated issue classification (blocker, tech debt, skippable)
Standardized specification-to-implementation mapping
Closed-loop auto-resolution logic for critical blockers

Use Cases

Setting up automated visual regression and verification pipelines
Creating proof-of-value reports for stakeholders with visual documentation
Validating a new feature implementation against its design specification

About

Key Features

Visual verification via multi-stage screenshot capture points
Comprehensive review artifact generation with visual proof
1 GitHub stars
Automated issue classification (blocker, tech debt, skippable)
Standardized specification-to-implementation mapping
Closed-loop auto-resolution logic for critical blockers

Use Cases

Setting up automated visual regression and verification pipelines
Creating proof-of-value reports for stakeholders with visual documentation
Validating a new feature implementation against its design specification