codebase-overview

Name: codebase-overview
Availability: InStock
Author: notque

Analyze a repository's type, language, and architecture into a markdown report.

415|44|Updated Mar 18, 2026

Search Tags:#architecture #documentation #onboarding #codebase #evidence #exploration #phased-discovery

Ready to run

npx skills add https://github.com/notque/claude-code-toolkit --skill codebase-overview-notque

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-overview
Source: https://github.com/notque/claude-code-toolkit/tree/main/skills/codebase-overview
Command: npx skills add https://github.com/notque/claude-code-toolkit --skill codebase-overview-notque

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic, evidence-backed codebase overviews reduce onboarding time by providing a clear, structured understanding of a new project, its structure, and key components.

Core Features & Use Cases

Four-phase discovery: Detect project type, explore key files, map architecture, and summarize findings with file-level evidence.
Entry point and module mapping: Identify main bootstrapping files, core modules, data models, and API surfaces.
Onboarding-ready report: Generates a structured markdown document with absolute paths and citations to observed files, ideal for new contributors.

Quick Start

Ask Claude to analyze the target repository with this skill to produce a complete onboarding-ready codebase overview.

Frequently Asked Questions about codebase-overview

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

FAQPage Schema

How do I generate a codebase overview for new contributor onboarding?▼

You generate an onboarding-ready codebase overview by applying a four-phase discovery process—DETECT, EXPLORE, MAP, SUMMARIZE—to surface entry points, core modules, data models, and API surfaces with file-level evidence in a structured markdown report.

What is the best way to identify entry points and core modules in an unfamiliar repository?▼

Identifying entry points and core modules requires mapping the repository's architecture through a phased discovery process that surfaces main bootstrapping files, data models, and API surfaces backed by absolute file path citations.

Does codebase discovery work without installing external dependencies or components?▼

Yes, codebase discovery operates with zero external dependencies or components, relying on an advanced internal reasoning design to systematically analyze the repository and produce evidence-backed architectural summaries.

Can I map a project's API surfaces and data models from existing code alone?▼

Yes, you map API surfaces and data models from existing code through the EXPLORE and MAP phases, which analyze repository files to extract structural evidence and cite specific absolute paths for architectural claims.

What is included in an onboarding-ready codebase summary report?▼

An onboarding-ready codebase summary report includes detected project type and language, mapped entry points, core modules, configuration, and tests, all presented as evidence-backed claims with absolute file paths in structured markdown format.

When should I use systematic codebase exploration instead of manually reading source files?▼

Use systematic codebase exploration when onboarding new contributors to complex architectures, replacing manual file reading with a structured four-phase methodology that guarantees evidence-backed architectural mapping and faster ramp-up.