meta-cognition-parallel

Analyze developer questions across language, design, and domain layers to produce architectural recommendations.

1|Updated Mar 20, 2026
One-click install
npx skills add https://github.com/kaynetik/skills --skill meta-cognition-parallel-kaynetik
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: meta-cognition-parallel
Source: https://github.com/kaynetik/skills/tree/main/meta-cognition-parallel
Command: npx skills add https://github.com/kaynetik/skills --skill meta-cognition-parallel-kaynetik

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the difficulty of diagnosing complex technical questions by running simultaneous, focused analyses across language mechanics, design choices, and domain constraints, then synthesizing a coherent, domain-correct recommendation.

Core Features & Use Cases

  • Three-Layer Analysis: Separates language-level mechanics, architecture/design trade-offs, and domain-specific constraints into distinct analyzers for clearer reasoning.
  • Parallel Agent Mode & Inline Fallback: Uses external agent prompts for true parallel execution when available, or performs sequential inline analysis when agents are not present.
  • Cross-Layer Synthesis: Merges results into a single actionable recommendation with confidence assessments, useful for fixing Rust borrow errors, choosing concurrency patterns for web services, or aligning design with regulatory constraints.

Quick Start

/meta-parallel Trading system reports E0382, was the trade record moved and what is the domain-correct fix?

Frequently Asked Questions about meta-cognition-parallel

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

FAQPage Schema
How do I diagnose complex Rust borrow checker errors like E0382 in architectural design?

Complex Rust borrow errors require isolating language mechanics from design trade-offs and domain constraints. A three-layer parallel analysis evaluates move semantics, architectural impacts, and domain rules simultaneously to synthesize a domain-correct fix with confidence assessments.

What is the best way to analyze design trade-offs for concurrency patterns in web services?

Concurrency design trade-offs are best analyzed by separating language mechanics, architectural choices, and domain constraints into distinct analyzers. This parallel three-layer approach synthesizes cross-layer recommendations with confidence assessments for robust architectural decisions.

Can I run parallel code analysis without external agent plugins?

Yes, parallel code analysis falls back to sequential inline analysis when external agent plugins are absent. The system still performs the three-layer meta-cognition analysis across language mechanics, design choices, and domain constraints, synthesizing cross-layer recommendations without requiring agent files.

When do I need domain-specific constraint analysis for API design?

Domain-specific constraint analysis for API design is needed when programming diagnostics must align with regulatory or business rules. Separating domain constraints from language mechanics and architecture trade-offs ensures synthesized recommendations satisfy both technical correctness and domain requirements.

Does meta-cognition parallel analysis support debugging Rust move semantics and ownership errors?

Yes, this parallel analysis method supports debugging Rust move semantics by evaluating language mechanics, design trade-offs, and domain constraints in three distinct layers. It synthesizes cross-layer results into a domain-correct architectural recommendation with confidence assessments.