learnings-researcher

Search frontmatter metadata in docs/solutions/ to surface past software solutions.

Updated Feb 16, 2026
One-click install
npx skills add https://github.com/praburajasekaran/ruthva-clinic-os --skill learnings-researcher-praburajasekaran
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: learnings-researcher
Source: https://github.com/praburajasekaran/ruthva-clinic-os/tree/main/.gemini/skills/learnings-researcher
Command: npx skills add https://github.com/praburajasekaran/ruthva-clinic-os --skill learnings-researcher-praburajasekaran

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The learnings-researcher Skill solves the problem of time-consuming and inefficient research into institutional knowledge for software development projects, ensuring that team members don't repeat known mistakes and benefit from existing learnings.

Core Features & Use Cases

  • Automated Knowledge Discovery: Surfaces relevant past solutions by searching the 'docs/solutions/' directory for relevant learnings.
  • Feature/Task Specific Research: Allows searching based on feature descriptions or tasks to identify related solutions quickly.
  • Search Strategy: Utilizes grep for pre-filtering based on keywords in frontmatter, minimizing tool calls for efficiency.

Quick Start

Use the learnings-researcher Skill before starting work on a feature to discover past solutions relevant to the task at hand.

Frequently Asked Questions about learnings-researcher

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search past software development solutions to avoid repeating mistakes?▼

To search past software development solutions, you can use automated knowledge discovery to grep frontmatter metadata within a dedicated docs directory, surfacing proven patterns and known issues before new feature development.

What is the best way to discover institutional knowledge before fixing a bug?▼

Discovering institutional knowledge before bug fixing is best handled by searching feature descriptions or tasks against past solutions, efficiently pre-filtering metadata to identify known issues and leverage existing learnings.

How do I find past solutions relevant to a specific feature task?▼

To find past solutions for a specific feature task, execute a search strategy that grep-filters frontmatter keywords in your solutions directory, efficiently surfacing relevant institutional knowledge without excessive tool calls.

Does this knowledge discovery approach require a specific directory structure?▼

This knowledge discovery approach requires a docs/solutions/ directory containing files with frontmatter metadata, enabling the grep-based pre-filtering strategy to accurately surface past software solutions for your queries.

Can I use grep to pre-filter institutional knowledge for software development?▼

Yes, you can use grep to pre-filter institutional knowledge for software development by searching frontmatter metadata keywords, a strategy designed to minimize tool calls and efficiently surface relevant past solutions.

Why should I search for existing learnings before starting new feature development?▼

You should search for existing learnings before new feature development to prevent repeating known mistakes, efficiently discovering proven patterns and past solutions through metadata pre-filtering instead of redundant troubleshooting.