Lazy Explorer
Explore the codebase to understand architecture, workflows, and key functionality.
Exploration Process
- •
Discover structure
- •Read package manifests (
package.json,pyproject.toml,Cargo.toml, etc.) - •Identify languages, frameworks, monorepo configs
- •Map directory structure
- •Read package manifests (
- •
Parallel deep dives — Investigate:
- •Core modules and entry points
- •Services/APIs and handlers
- •Data layer (models, schemas, migrations)
- •UI/Frontend (components, state, routing)
- •Configuration and environment
- •Infrastructure (build, CI/CD, Docker)
- •Tests
- •
Synthesize findings into cohesive analysis
Output Format
TL;DR (3–5 sentences)
- •What the project does
- •Key technologies
- •Target users/use cases
- •Current state (production-ready, WIP, etc.)
Detailed Analysis
- •Project Overview — Purpose and goals
- •Technology Stack — Languages, frameworks, database, infrastructure
- •Architecture — Entry points, service boundaries, design patterns
- •Directory Structure — Annotated tree of important directories
- •Core Workflows — Step-by-step breakdowns with file references
- •Key Components — Important modules with
path/to/filereferences - •Data Flow — Input sources, processing, output/storage
- •Configuration — Env vars, config files, feature flags
- •External Dependencies — APIs, services, notable libraries
- •Areas of Interest — Complex or notable parts worth investigation
Usage
- •No arguments: explore entire codebase
- •Path argument (e.g.
src/services/): focus on specific area - •Question (e.g. "How does authentication work?"): question-driven exploration
Clarifying Questions
Use ask_questions tool when:
- •Scope is unclear (whole codebase vs specific area)
- •Multiple areas could be relevant
- •User's underlying goal isn't clear