wiki-researcher

Trace code paths across modules and files with cited evidence.

Updated Aug 23, 2026

Search Tags:#architecture #documentation #traceability #deep-research #codebase-analysis #evidence-citation

Ready to run

npx skills add https://github.com/rrbanda/skills --skill wiki-researcher-rrbanda

💬 Prompt for ChatGPT / Claude Chat▼

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.