learnings-researcher

To retrieve past solutions and prevent repeated mistakes, use grep-first parallel content filtering to quickly narrow down relevant documented institutional solutions from your knowledge base. This avoids scanning every file and surfaces proven patterns for your current software engineering task.

Knowledge retrieval ranks institutional learnings by scoring solution relevance to your current task. It surfaces high-severity critical patterns and applicable gotchas first, ensuring technical planning prioritizes the most impactful past solutions and mistake avoidance strategies.

Yes, you need access to a structured docs/solutions/ directory containing YAML-frontmatter solution files and a critical patterns reference. This structured format is required to filter and rank applicable institutional learnings effectively.

Search a knowledge base for bug fix planning and feature development during pre-implementation research. Retrieving institutional learnings before writing code helps identify integration pitfalls, caching issues, and API bugs to avoid common errors and delayed timelines.

The best way to avoid reinventing solved problems is implementing efficient grep-first search across documented solutions. This applies parallel content filtering to quickly find relevant past solutions and critical patterns, preventing avoidable errors and reusing proven patterns.