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ai-dev-research

Produce citation-rich AI research reports on RAG architectures and agent workflows.

2|Updated Jan 24, 2026
Search Tags:#research#embeddings#RAG#agents#citations#ai-dev#knowledge-synthesis
One-click install
npx skills add https://github.com/swannysec/robot-tools --skill ai-dev-research
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-dev-research
Source: https://github.com/swannysec/robot-tools/tree/main/research-toolkit/skills/ai-dev-research
Command: npx skills add https://github.com/swannysec/robot-tools --skill ai-dev-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides world-class, citation-rich AI research outputs for AI-enabled software development, reducing time spent locating authoritative sources and synthesizing complex topics.

Core Features & Use Cases

  • Deep technical research synthesis across papers, docs, and practitioner sources.
  • Technical consultation on AI architectures, tool selection, and implementation approaches.
  • Implementation guidance with production-ready patterns and best practices.
  • Comparative analysis of AI frameworks, models, and services.
  • Current state-of-the-art analysis with authoritative citations.

Quick Start

Use this skill to request a research report on RAG architectures, including executive summary, deep-dive, and citations.

Frequently Asked Questions about ai-dev-research

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

FAQPage Schema
How do I research RAG architectures and get citations for AI software development?▼

You can research RAG architectures by requesting structured outputs with executive summaries, technical deep-dives, and actionable recommendations annotated with authoritative sources and URLs.

What is the best way to compare LLM integration frameworks and agent workflows?▼

Comparing LLM integration frameworks and agent workflows is done through comparative analysis of AI frameworks, models, and services, delivering production-ready patterns and best practices.

How do I synthesize technical research on embeddings across primary sources and official docs?▼

Synthesizing technical research on embeddings involves deep technical research synthesis across papers, official docs, and practitioner sources to reduce time spent locating authoritative sources.

Does this AI research skill provide implementation guidance for production-ready patterns?▼

Yes, this AI research skill provides implementation guidance with production-ready patterns and best practices alongside technical consultation on AI architectures and tool selection.

Can I get a current state-of-the-art analysis on AI tooling with authoritative citations?▼

Yes, you can get current state-of-the-art analysis with authoritative citations covering AI tooling, LLM integration, and agent workflows annotated with sources and URLs.

What are the limitations of using automated research synthesis for AI development topics?▼

Automated research synthesis for AI development topics focuses on RAG architectures, agent workflows, LLM integration, and embeddings, meaning topics outside this scope require alternative research approaches.

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