When should I use Research-Deep 150?

Trigger this skill when facing high-stakes decisions like choosing a framework, investigating intermittent bugs, or understanding legacy code where the reasoning isn't immediately obvious.

How does this skill utilize Git history?

It uses git blame, logs, and commit history to uncover the 'why' behind specific implementation choices, helping to preserve original intent when refactoring or debugging.

What is the 150% Research Rule?

It is a methodology that requires 100% research from primary sources (like your code or official docs) plus a 50% enhancement check from the 'other world' (external if you started internal, and vice versa) to ensure accuracy.

What kind of output does this skill produce?

It generates a structured 'Research-Deep 150 Complete' report featuring internal findings, external evidence, a synthesized conclusion, and a confidence percentage.

Deep Technical Research

Name: Deep Technical Research
Author: MykhailoDmytriakha

byMykhailoDmytriakha

Learning & Documentation

Performs comprehensive investigations by synthesizing internal codebase context with external world knowledge to provide verified technical solutions.

About

The Research-Deep 150 protocol ensures that technical inquiries are validated through a multi-dimensional approach. By applying the '150% Research Rule,' this skill forces a cross-check between internal project data—such as Git history, logs, and existing code patterns—and external resources like official documentation, community forums, and industry best practices. This dual-source methodology is designed to eliminate single-source bias, providing developers with high-confidence recommendations for architectural decisions, library selection, and complex bug resolution.

Key Features

Integrates web search patterns to identify community-proven solutions and common pitfalls.
Synthesizes internal code context with external web documentation and best practices.
0 GitHub stars
Analyzes Git history and commit logs to identify original intent and architectural evolution.
Applies the 150% Research Rule to cross-validate findings across multiple environments.
Provides structured research reports with quantified confidence levels and source quality ratings.

Use Cases

Debugging complex issues by correlating internal application logs with known external CVEs or GitHub issues.
Defining architectural patterns that align with existing project constraints and modern industry standards.
Evaluating and selecting new libraries by comparing internal compatibility with external ecosystem health.

About

Key Features

Integrates web search patterns to identify community-proven solutions and common pitfalls.
Synthesizes internal code context with external web documentation and best practices.
0 GitHub stars
Analyzes Git history and commit logs to identify original intent and architectural evolution.
Applies the 150% Research Rule to cross-validate findings across multiple environments.
Provides structured research reports with quantified confidence levels and source quality ratings.

Use Cases

Debugging complex issues by correlating internal application logs with known external CVEs or GitHub issues.
Defining architectural patterns that align with existing project constraints and modern industry standards.
Evaluating and selecting new libraries by comparing internal compatibility with external ecosystem health.