wiki-researcher

Trace code paths across modules and files with cited evidence.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/rrbanda/skills --skill wiki-researcher-rrbanda
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: wiki-researcher
Source: https://github.com/rrbanda/skills/tree/main/skills/documentation/wiki-researcher
Command: npx skills add https://github.com/rrbanda/skills --skill wiki-researcher-rrbanda

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants to understand how something works across multiple files, or asks for comprehensive analysis of a specific system or pattern.

Core Features & Use Cases

  • Iterative, multi-turn investigation that traces code paths across modules, files, and repositories.
  • Generates evidence-backed findings with line-referenced sources and citation formatting.
  • Use Case: architectural evaluation, pattern discovery, and cross-file comprehension to inform refactoring or documentation.

Quick Start

Prompt the agent to start a deep, multi-file investigation of a topic across your codebase.

Frequently Asked Questions about wiki-researcher

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

FAQPage Schema
How do I trace data flow and architectural patterns across multiple codebase files?

Cross-file codebase tracing requires multi-turn iterative investigations that map data flow across modules and repositories. This deep research approach generates evidence-backed findings with line-referenced sources and formal citation formatting to ensure architectural pattern discovery is fully traceable.

What is the best way to document codebase architecture with traceable evidence?

Architectural documentation with traceable evidence requires deep codebase research that collects line-referenced sources and formal citations. By performing iterative investigations across files, you generate evidence-grounded findings that establish clear traceability for architectural evaluation and pattern discovery.

Can I use deep codebase research for evaluating refactoring impacts across large repositories?

Deep codebase research evaluates refactoring impacts by tracing code paths and data flow across large repositories. Through multi-turn iterative investigation with formal findings and traceable citations, it comprehensively analyzes cross-file dependencies to inform architectural refactoring decisions.

Does multi-file codebase analysis require any specific dependencies or environment setup?

Multi-file codebase analysis requires no external dependencies or environment setup. You simply prompt the agent to start a deep investigation of a topic across your codebase, and it autonomously performs iterative research with zero tolerance for shallow analysis.

Why does codebase pattern investigation need iterative reporting with multiple iterations?

Codebase pattern investigation needs iterative reporting because complex cross-file tracing requires progressive refinement across five iterations. This disciplined evidence collection approach ensures zero tolerance for shallow analysis, producing formal findings with line-referenced sources and traceable citations.