How does it ensure the accuracy of the research findings?

The skill follows a strict evidence-based methodology, requiring all findings to include specific file and line-range references. It also uses parallel agents to provide overlapping validation of findings.

Can this skill access external documentation or APIs?

Yes, it includes a conditional web-search-researcher agent that can be activated when external technical context or third-party library documentation is required for the investigation.

How does the Comprehensive Research skill differ from a standard grep search?

Unlike basic keyword searching, this skill uses specialized agents to interpret context, identify implementation patterns, and synthesize findings into high-level architectural insights with cross-referenced evidence.

Does it support caching to save on processing time?

Yes, the skill implements a hierarchical caching strategy that stores successful coordination strategies, pattern recognition results, and effective agent combinations to improve response times.

Comprehensive Research

Name: Comprehensive Research
Author: v1truv1us

byv1truv1us

生产力与工作流

Orchestrates multi-phase technical investigations across codebases and documentation using specialized agents for deep architectural insights.

关于

The Comprehensive Research skill is a systematic orchestration framework designed to help developers navigate and understand complex codebases. By coordinating parallel discovery agents and sequential deep-analysis agents, it transforms raw source code and documentation into structured insights, complete with file-level evidence, identified implementation patterns, and actionable recommendations. It is an essential tool for onboarding onto new projects, performing impact analysis for major refactors, or resolving complex architectural questions that require cross-referencing multiple files and historical context.

主要功能

Multi-phase orchestration including Discovery, Analysis, and Synthesis
Hierarchical caching strategy for high-performance repeat investigations
Parallel agent execution for rapid codebase and documentation scanning
Architectural pattern identification and historical context analysis
0 GitHub stars
Evidence-based reporting with specific file and line-number references

使用场景

Performing technical impact analysis before major architectural refactors
Onboarding to legacy codebases by identifying core design patterns and decisions
Analyzing complex feature implementations across microservices or large repositories

关于

主要功能

Multi-phase orchestration including Discovery, Analysis, and Synthesis
Hierarchical caching strategy for high-performance repeat investigations
Parallel agent execution for rapid codebase and documentation scanning
Architectural pattern identification and historical context analysis
0 GitHub stars
Evidence-based reporting with specific file and line-number references

使用场景

Performing technical impact analysis before major architectural refactors
Onboarding to legacy codebases by identifying core design patterns and decisions
Analyzing complex feature implementations across microservices or large repositories