How does the three-layer analysis work?

The skill evaluates Language Mechanics (syntax and compiler rules), Design Choices (patterns and structure), and Domain Constraints (industry-specific requirements) to provide a complete answer.

Is this skill suitable for production use?

This is currently an experimental skill (v0.1.0) intended for testing advanced AI reasoning patterns in Rust development environments.

What makes this skill 'parallel'?

It uses Claude's fork capability to run three specialized sub-agents simultaneously, analyzing different aspects of your problem at once rather than in a linear sequence.

Can this help with specific Rust errors like E0382?

Yes, it is specifically designed to analyze borrow checker moves and lifetimes by determining if the fix should be at the implementation (Clone) or architectural (Arc) level.

Rust Parallel Meta-Analysis

Name: Rust Parallel Meta-Analysis
Author: actionbook

byactionbook

•

596

Developer Tools

Analyzes complex Rust development challenges using a three-layer parallel cognitive framework to provide domain-aware architectural solutions.

About

This experimental skill optimizes problem-solving by launching three specialized sub-agents in parallel to evaluate Rust code through the lenses of language mechanics, design patterns, and domain-specific constraints. By synthesizing these perspectives simultaneously rather than sequentially, it helps developers resolve intricate compiler errors and architectural dilemmas while ensuring the final solution aligns with both Rust's safety guarantees and the specific requirements of the application domain, such as high-frequency trading or concurrent web services.

Key Features

596 GitHub stars
Parallel three-layer cognitive analysis using context forking
Automated sub-agent orchestration for mechanics, design, and domain
Domain-specific constraint integration for trading, web, and CLI
Detailed reasoning chains linking language features to design patterns
Cross-layer synthesis for holistic architectural recommendations

Use Cases

Troubleshooting complex borrow checker errors in high-performance systems
Determining optimal architectural patterns for CLI tools with complex configuration priorities
Designing thread-safe shared state for concurrent web applications

About

Key Features

596 GitHub stars
Parallel three-layer cognitive analysis using context forking
Automated sub-agent orchestration for mechanics, design, and domain
Domain-specific constraint integration for trading, web, and CLI
Detailed reasoning chains linking language features to design patterns
Cross-layer synthesis for holistic architectural recommendations

Use Cases

Troubleshooting complex borrow checker errors in high-performance systems
Determining optimal architectural patterns for CLI tools with complex configuration priorities
Designing thread-safe shared state for concurrent web applications