What is the Tree of Thoughts (ToT) methodology?

ToT is an advanced reasoning protocol where the AI simulates three distinct experts (Architect, Security, and Performance) who generate, challenge, and refine hypotheses to ensure no hidden bugs or side effects are missed.

Does the output show all the internal expert debates?

No, the skill performs the complex reasoning internally to keep the final report clean and actionable, providing only the consolidated risk levels and prioritized action items.

Can it analyze staged changes before a commit?

Yes, the skill supports 'commit', 'branch', and 'staged' analysis modes to help you evaluate the impact of your work at any stage of the development lifecycle.

How does the complexity score work?

The skill assigns points based on specific criteria: API signature changes (+2), type definition changes (+2), security-related logic (+3), and complex conditionals (+1). A score of 3 or higher triggers advanced Tree of Thoughts analysis.

Code Impact Evaluator

Name: Code Impact Evaluator
Author: vincent-kk

byvincent-kk

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Collaboration Tools

Analyzes code changes using Tree of Thoughts methodology to assess risk levels and identify downstream impacts.

About

The Code Impact Evaluator skill transforms Claude into an expert reviewer capable of navigating complex codebases and high-stakes changes. By utilizing a sophisticated complexity scoring system and the Tree of Thoughts (ToT) methodology—including both Breadth-First and Depth-First search strategies—it identifies direct and indirect risks across API signatures, type definitions, and security-critical logic. This skill is essential for large-scale refactorings or mission-critical updates where manual review might miss cascading effects, providing a structured output of Must, Should, and Consider action items to ensure stability and maintainability.

Key Features

Automated complexity scoring based on API, Type, and Security changes
Three-stage Tree of Thoughts (ToT) analysis for deep reasoning on complex logic
1 GitHub stars
Multi-expert consensus model (Architect, Security, Performance) for risk assessment
Categorization of changes into refactoring, logic updates, and file movements
Prioritized action items (Must/Should/Consider) for streamlined remediation

Use Cases

Streamlining the pull request process by automatically identifying high-risk areas and migration needs
Conducting deep-dive risk assessments for security-critical or performance-heavy code sections
Evaluating the ripple effects of changing public API signatures or shared TypeScript definitions

About

Key Features

Automated complexity scoring based on API, Type, and Security changes
Three-stage Tree of Thoughts (ToT) analysis for deep reasoning on complex logic
1 GitHub stars
Multi-expert consensus model (Architect, Security, Performance) for risk assessment
Categorization of changes into refactoring, logic updates, and file movements
Prioritized action items (Must/Should/Consider) for streamlined remediation

Use Cases

Streamlining the pull request process by automatically identifying high-risk areas and migration needs
Conducting deep-dive risk assessments for security-critical or performance-heavy code sections
Evaluating the ripple effects of changing public API signatures or shared TypeScript definitions