toilahuongg/shopify-agents-kit

research

Guide for conducting thorough and synthesized research, focusing on verification, multi-source analysis, and RAG patterns.

First seen Mar 3, 2026

Installation

$ npx skills add toilahuongg/shopify-agents-kit --skill research

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from toilahuongg/shopify-agents-kit · top by installs.

npx skills add toilahuongg/shopify-agents-kit

Browse all from toilahuongg/shopify-agents-kit

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 10
License LICENSE
Default branch master
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,760 B
  • docs SUMMARY.md 138 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 7 installs

SKILL.md

Research Skill

This skill outlines the process for conducting deep, accurate, and synthesized research. It transforms the agent from a simple search engine interface into a comprehensive research assistant.

🕵️ Core Philosophy

  • Synthesis over Summarization: Don't just list search results. Combine information to answer the "So What?".
  • Triangulation: Verify facts by finding them in multiple independent sources.
  • Citation is Mandatory: Every specific claim must be backed by a source.

🛠️ The Research Framework

1. Planning (The "Research Agent" Mode)

Before searching, define the scope.

  • Clarify Objectives: What is the exact question?
  • Identify Domains: Where does this information live? (Academic papers, technical docs, news, forums?)
  • Keyword Strategy: Generate diverse search queries to target different aspects (e.g., broad vs. specific, technical vs. layman).

2. Information Gathering (Source Quality)

  • Primary Sources: Official documentation, direct interviews, laws, scientific papers.
  • Secondary Sources: Reputable analysis, industry reports, expert articles.
  • Tertiary Sources: Wikipedia, generalized blog posts (use only for initial context).

Rule: If a search result contradicts the user's premise, investigate the discrepancy explicitly.

3. Synthesis & Analysis (RAG Pattern)

When presenting findings:

  1. The Executive Summary: Answer the question directly in 1-2 paragraphs.
  2. Key Findings: Group facts by theme, not by source.

Bad: "Source A says X. Source B says Y." Good: "The consensus on Topic X is [...], although some experts disagree regarding [...] (Source B)."

  1. Evidence Table: If comparing options, always use a table.

4. Verification & Fact-Checking

  • Check Dates: Is this info outdated? (Critical for tech/laws).
  • Cross-Reference: If one source makes a bold claim, find a second source to confirm.
  • Identify Bias: Note if a source has a conflict of interest (e.g., a vendor review).

🚀 Execution Patterns

for "Deep Dive" Requests:

  1. Search for the core concept.
  2. Read the top results to understand the vocabulary.
  3. Refine search with specific technical terms found in step 2.
  4. Synthesize findings into a structured report.

for "Tech Stack Comparison":

  1. Identify criteria (e.g., Performance, Cost, DX).
  2. Search for specific comparisons (e.g., "Mongoose vs Prisma performance").
  3. Create a comparison matrix.
  4. Provide a recommendation based on specific use cases.