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jugrajsingh
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researching

Decompose codebase questions into sub-questions for parallel locator, analyzer, and pattern-finder agents.

1|Updated Jan 31, 2026
Search Tags:#documentation#research#parallel processing#agent#reporting#codebase analysis
One-click install
npx skills add https://github.com/jugrajsingh/skillgarden --skill researching-jugrajsingh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: researching
Source: https://github.com/jugrajsingh/skillgarden/tree/main/plugins/researcher/skills/researching
Command: npx skills add https://github.com/jugrajsingh/skillgarden --skill researching-jugrajsingh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates in-depth codebase research by decomposing complex questions, dispatching specialized AI agents in parallel, and synthesizing their findings into a structured, citable report.

Core Features & Use Cases

  • Decomposition: Breaks down broad research questions into specific, actionable sub-questions.
  • Parallel Agent Dispatch: Utilizes 'locator', 'analyzer', and 'pattern-finder' agents concurrently for efficient information gathering.
  • Persistent Reporting: Generates detailed reports with file:line citations, ensuring verifiability and aiding future reference.
  • Use Case: When investigating a new feature's implementation, use this Skill to pinpoint relevant files, understand data flow, and identify existing patterns, all synthesized into a single, easy-to-understand document.

Quick Start

Use the researching skill to find out how authentication works in the project.

Frequently Asked Questions about researching

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

FAQPage Schema
How do I conduct parallel codebase research to understand a new feature's implementation?▼

Parallel codebase research decomposes broad questions into sub-questions, dispatching locator, analyzer, and pattern-finder agents concurrently to pinpoint files, understand data flow, and synthesize findings into a single document.

What is the best way to generate citable documentation for complex codebase questions?▼

Generating citable documentation involves synthesizing parallel agent findings into a persistent report with file:line references, ensuring verifiability and aiding future reference for complex codebase questions.

Can I use multi-agent research to analyze data flow and identify existing patterns in my project?▼

Yes, multi-agent research uses locator, analyzer, and pattern-finder agents concurrently to analyze data flow and identify existing patterns, synthesizing the findings for comprehensive understanding.

How does codebase analysis work when investigating unfamiliar code structure?▼

Codebase analysis works by breaking down broad research questions into specific sub-questions, dispatching specialized AI agents in parallel to gather information, and synthesizing their findings into a structured report.

Do I need any external dependencies to run parallel research agents on my codebase?▼

No external dependencies are required. The parallel research process operates independently to decompose queries, dispatch agents, and generate detailed reports with file:line citations.

When should I not use a multi-agent approach for codebase analysis?▼

You should avoid multi-agent codebase analysis for simple, single-file queries where the overhead of decomposing questions and dispatching parallel agents outweighs the benefit of synthesized reporting.

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