search-first

To research existing libraries before writing custom code, systematically search package registries like npm or PyPI, GitHub repositories, and MCP servers to find proven solutions. This workflow evaluates maintenance status, documentation quality, and license terms to select the optimal implementation path.

Evaluate open source dependencies by checking their functionality, maintenance status, community support, documentation quality, license compatibility, and dependency overhead. This evaluation determines whether to adopt, extend, compose, or build a custom solution based on candidate quality.

You should avoid reusing existing open source tools and build a custom solution when candidate packages fail your evaluation criteria for maintenance status, community support, documentation quality, license compatibility, or when dependency overhead outweighs the functionality benefits.

The search-first approach to tool selection works across any programming language or framework. It applies to all software development tasks including new feature creation, dependency integration, utility development, and third-party service adoption, ensuring code reuse over redundant custom development.

The best way to integrate third-party services without technical debt is to research existing tools and libraries before implementation. By evaluating candidate solutions against functionality and maintenance status, you adopt proven patterns instead of writing redundant custom code.

To choose between adopting or extending an existing package for utility development, use a decision matrix comparing candidate quality, maintenance status, and license compatibility. This matrix clarifies whether to adopt, extend, compose, or build a custom solution.