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To find existing libraries and patterns before writing new code, initiate a pre-implementation research pass to surface candidate tools and evaluate dependencies. This systematized workflow triggers a researcher agent to gather options, helping you avoid reinventing the wheel and proceed with informed decisions.

The best way to evaluate dependencies for a new software feature is to enforce a documented research workflow that proactively surfaces available APIs and reusable components. This early evaluation reduces risk by ensuring you choose well-supported, compatible solutions before implementation.

You should research reusable components before starting feature development because proactive research reduces engineering risk and saves time. By systematizing the exploration of existing tools and patterns, you avoid reinventing the wheel and select well-supported solutions for your project.

You systematize engineering-workflow research for decision-making by codifying a pre-implementation research phase that uses a researcher agent. This agent gathers insights on existing tools and libraries, supporting informed decisions and ensuring early evaluation of options before you commit to coding.

This research workflow requires no specific external tools or environments to run, as it operates without dependencies. It coordinates upfront research internally by triggering a researcher agent to document candidate tools and patterns before you write new code.

You should avoid using a pre-implementation research pass when your feature development requires immediate deployment without the overhead of evaluating dependencies or reusable components. If existing patterns are already fully documented and chosen, triggering another research workflow adds unnecessary friction.