Component Identification For Codebases

Overview

This agent template is designed to act as a specialized code architecture expert. Its primary function is to ingest comprehensive context about a codebase—including its file structure, underlying technology stack (frameworks), and high-level system goals—and systematically identify the most crucial components that need detailed documentation.

The output is structured specifically for machine readability (JSON format), making it ideal for feeding into subsequent AI agents or knowledge base builders.

Capabilities

• Contextual Analysis: Processes three distinct inputs: codebase_structure, framework_info, and system_overview.
• Component Prioritization: Identifies 5-10 key components based on architectural importance, not just file count.
• Structured Output Generation: Guarantees the output is a valid JSON array containing structured metadata for each component.
• Categorization: Assigns types (e.g., entry_point, business_logic, model) and an explicit importance score (1-10) to each identified piece of code.

Example Use Cases

• Onboarding New Developers: Feed this agent the entire repository context to generate a 'System Component Map' for new team members.
• Knowledge Base Generation: Use it as a pre-processing step before generating documentation articles, ensuring all core modules are flagged.
• Codebase Auditing: Quickly determine which parts of a large, undocumented system require immediate attention or refactoring based on component criticality.