Analyzing Projects

What it does

This skill analyzes project details to help AI agents understand unfamiliar codebases and workflows. It systematically explores a project's structure, identifies its technology stack (including programming languages, frameworks, and infrastructure), and maps out key patterns like architecture and API style. The analysis follows a six-step checklist designed for efficient onboarding and comprehension of new projects.

When to use it

• When starting work on a new project where the codebase is unfamiliar.
• To quickly understand the technology stack used in an existing project.
• During code exploration or when needing to grasp the overall structure of a project.
• To answer "how does this work" questions about a project's functionality.

Key capabilities

• Tech Stack Detection: Identifies programming languages, package managers (e.g., package.json, requirements.txt), frameworks (e.g., React, Django), and infrastructure components (e.g., Dockerfiles, Kubernetes).
• Project Structure Mapping: Presents a tree-like representation of the project's directory structure with annotations describing each section’s purpose.
• Pattern Identification: Recognizes architectural patterns (Monolith, Microservices) and API styles (REST, GraphQL).
• Progress Tracking: Uses a checklist to guide the analysis process, ensuring all key areas are examined.

Example prompts

• "Analyze this project and tell me what technologies it uses."
• "Can you map out the structure of this codebase?"
• "What is the architecture of this project?"
• "Walk me through a quick overview of this project, starting with the README."

Tips & gotchas

• The skill relies on common file markers like README.md, package.json, and Dockerfiles to identify key aspects of the project. Ensure these files are present for optimal results.
• This skill is designed for understanding existing projects, not for creating new ones or contributing directly to development.