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codebase-research

Decompose codebase queries into parallel sub-agent research tasks and synthesize structured reports.

17|1|Updated Dec 7, 2025
Search Tags:#automation#architecture#research#codebase#analyze#live-references
One-click install
npx skills add https://github.com/mhylle/claude-skills-collection --skill codebase-research-mhylle
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-research
Source: https://github.com/mhylle/claude-skills-collection/tree/main/skills/codebase-research
Command: npx skills add https://github.com/mhylle/claude-skills-collection --skill codebase-research-mhylle

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates thorough, reproducible codebase research by decomposing user questions into parallel sub-agent tasks and synthesizing findings into a single, coherent report.

Core Features & Use Cases

  • Parallel sub-agent orchestration: Spawns specialized agents (codebase-locator, codebase-analyzer, docs-locator, docs-analyzer) to explore different aspects concurrently, reducing turnaround time.
  • Live codebase tracing: Collects file paths, line references, and component interactions to map how the code works today.
  • Structured research outputs: Produces a multi-section document with architecture overview, component relationships, and design decisions when available.
  • Use Case: When asked how a feature works or where functionality resides, generates a comprehensive documentation plan with actionable findings.

Quick Start

Provide a research prompt such as: Explain how the data flow works for the payment feature in the codebase. The skill will decompose the request, spawn parallel agents, and deliver a structured report.

Frequently Asked Questions about codebase-research

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

FAQPage Schema
How do I analyze a codebase to understand how a feature works?▼

To analyze a codebase and understand how a feature works, the skill decomposes your query into parallel sub-agent tasks that trace live code references and synthesize findings into a structured architecture report.

What is the best way to research component interactions across a large codebase?▼

The best way to research component interactions is using parallel sub-agent orchestration, which spawns specialized agents to concurrently map file paths, line references, and relationships, delivering a comprehensive multi-section document.

How does multi-agent codebase research improve architecture documentation?▼

Multi-agent codebase research improves architecture documentation by spawning concurrent locator and analyzer agents that trace live code references, synthesizing the results into a precise overview of design decisions and component interactions.

Can I use automated research to find where specific functionality resides in my code?▼

Yes, you can use automated research to find where functionality resides by providing a research prompt; the system spawns parallel agents to trace live codebase references and map the exact locations within a structured report.

Do I need any dependencies to run parallel codebase research?▼

No dependencies are required to run parallel codebase research. The skill operates independently through its internal multi-agent orchestration workflow to decompose queries and generate structured documentation outputs.

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