Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 4 skills

Use this as a shortlist, then open the skill detail page before adopting.

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Decision summary

Graphify is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.

Strongest overall

Graphify

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

Graphify

Best first install candidate based on install readiness and adoption.

Freshest repo

Graphify

Most recent maintenance signal among this shortlist.

SignalSmart Llm Loader

smart-llm-loader is a lightweight yet powerful Python package that transforms any document into LLM-ready chunks. Spend less time on preprocessing headaches and more time building what matters. From RAG systems to chatbots to document Q&A, SmartLLMLoader handles the heavy lifting so you can focus on creating exceptional AI applications.

RAG Techniques

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

LightRAG

[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"

Graphify

AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph.

Quality
64/100
Promising
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
54/100
Needs manual review

Do a manual repository review before adding this to an agent workflow.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Adoption327 stars
0 installs
28K stars
0 installs
37K stars
0 installs
91K stars
0 installs
FreshnessNov 14, 2025Jun 17, 2026Jun 18, 2026Jul 18, 2026
Use-case fit
Workflow fit
Platform hintsPython, RAG, Claude Code, LangChainJupyter Notebook, Semantic Search, Claude Code, OpenAI Agents, LangChainPython, Knowledge Graph, Claude Code, OpenAI AgentsPython, Knowledge Graph, Claude Code, OpenAI Agents, Cursor
WarningsNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yet
Best forRAG and knowledge workflows · Claude Code teams · builders willing to evaluate younger projectsRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsCoding agents workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security review
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Install
$ npx skills add drmingler/smart-llm-loader
$ npx skills add NirDiamant/RAG_Techniques
$ npx skills add HKUDS/LightRAG
$ npx skills add safishamsi/graphify