bk-research

Research problem spaces and existing solutions to inform technology selection.

Updated Mar 3, 2026
One-click install
npx skills add https://github.com/dikini/knot --skill bk-research
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bk-research
Source: https://github.com/dikini/knot/tree/main/.agents/skills/bk-research
Command: npx skills add https://github.com/dikini/knot --skill bk-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you thoroughly investigate a problem space, understand existing solutions, and identify potential trade-offs before committing to a specific technical approach or architecture.

Core Features & Use Cases

  • Problem Space Exploration: Uncover the landscape of existing solutions, libraries, and best practices.
  • Technology & Architecture Evaluation: Compare different options based on defined criteria, assessing pros, cons, maturity, and complexity.
  • Use Case: Before starting a new feature that requires a complex data processing pipeline, use this Skill to research available libraries, compare their performance and integration effort, and recommend the most suitable one.

Quick Start

Research local LLM provider options for gadulka.

Frequently Asked Questions about bk-research

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

FAQPage Schema
How do I research existing solutions and trade-offs before technology selection?

To research existing solutions and trade-offs, gather evidence from web searches, package repositories, and documentation to produce comparative analyses that inform your technology selection.

What is the best way to evaluate architecture options for a novel problem space?

Evaluating architecture options for a novel problem space involves analyzing existing solutions and identifying potential trade-offs by gathering evidence from documentation and package repositories.

How do I compare libraries for a complex data processing pipeline?

Compare libraries for a complex data processing pipeline by gathering evidence from package repositories and documentation, assessing pros, cons, maturity, and complexity to recommend the most suitable option.

When do I need to investigate a problem space before committing to an architecture?

You need to investigate a problem space before committing to an architecture when facing novel problems or unfamiliar domains, ensuring you understand existing solutions and potential trade-offs.

Can I use web searches to explore unfamiliar technical domains and synthesize findings?

Yes, you can use web searches to explore unfamiliar technical domains, gathering evidence to analyze novel problems and produce synthesized findings that inform architecture decisions.

What are the limitations of using package repositories for technology evaluation?

Package repositories provide evidence for technology evaluation but may lack context on specific integration efforts, requiring additional documentation analysis to fully assess trade-offs and architectural fit.