ck:research

Research technical solutions and architectures with multi-source evidence and citations.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/MinhQuyen274/smartify --skill ck-research-minhquyen274
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ck:research
Source: https://github.com/MinhQuyen274/smartify/tree/main/Frontend_PROJECT_Figma/.opencode/skills/research
Command: npx skills add https://github.com/MinhQuyen274/smartify --skill ck-research-minhquyen274

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gemini, ck:docs-seeker, WebSearch.

What problem does it solve?

It solves the problem of making better engineering decisions by turning messy, unverified information into structured, evidence-backed solution research.

Core Features & Use Cases

  • Architecture and requirements research: scope a topic, define evaluation criteria, and gather relevant technical inputs for solution design.
  • Best-practices synthesis: consolidate patterns, tradeoffs, and recommendations focused on scalability, security, performance, and maintainability.
  • Cross-reference validation: verify claims across multiple independent sources and prioritize currency (last ~12 months when possible).

Quick Start

Ask the AI to run ck:research on a topic like "[topic]" and produce a timestamped research report with executive summary, security and performance findings, and cited resources.

Frequently Asked Questions about ck:research

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

FAQPage Schema
How do I evaluate technical architecture and requirements before making design decisions?

To evaluate technical architecture, scope the topic, define evaluation criteria, and gather technical inputs for solution design. This research process cross-validates claims across multiple independent sources to produce a cited markdown report with actionable recommendations.

What is the best way to discover engineering best practices for scalability and security?

Discovering engineering best practices for scalability and security involves consolidating patterns, tradeoffs, and recommendations from multiple independent sources. This synthesis prioritizes information from the last twelve months to ensure relevant analysis for modern engineering topics.

Can I use automated research to generate a cited report on system design tradeoffs?

Yes, you can generate a cited report on system design tradeoffs by running automated research. The process requires up to five tool calls for evidence gathering and cross-validation, outputting a timestamped markdown report with an executive summary and cited resources.

Does cross-reference validation help verify technology evaluation claims for modern systems?

Cross-reference validation verifies technology evaluation claims by checking them against multiple independent sources. This ensures that technical inputs for solution design are accurate and prioritizes currency, targeting data from the last twelve months when possible.

What are the limitations of using automated research for performance and maintainability analysis?

Limitations of automated performance and maintainability analysis include a strict dependency on up to five tool calls for evidence gathering and a reliance on web search availability. The analysis prioritizes data from the last twelve months, potentially missing older foundational context.