Star0

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.

Add more skills

Decision summary

Logseq is the strongest overall pick here because it has a 100/100 readiness score and fits RAG and knowledge.

Strongest overall

Logseq

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

Fastest prototype

Logseq

Best first install candidate based on install readiness and adoption.

Freshest repo

Logseq

Most recent maintenance signal among this shortlist.

SignalLlmgraph

Create knowledge graphs with LLMs

Llm Graph Builder

Neo4j graph construction from unstructured data using LLMs

Logseq

A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV

KAG

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

Quality
66/100
Promising
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
68/100
Prototype first

Prototype with this skill first; keep a fallback candidate ready.

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.

Adoption508 stars
0 installs
4.8K stars
0 installs
43K stars
0 installs
8.8K stars
0 installs
FreshnessOct 11, 2025Jun 18, 2026Jun 19, 2026Jan 28, 2026
Use-case fit
RAG and knowledgeCoding agentsWorkflow automation
RAG and knowledgeCoding agentsBrowser automation
RAG and knowledgeGitHub automationCoding agents
RAG and knowledgeBrowser automationCoding agents
Stack fit
RAG knowledge baseContent growth agent
RAG knowledge baseContent growth agent
RAG knowledge baseContent growth agent
RAG knowledge baseBrowser QA agent
Platform hintsJupyter Notebook, Knowledge Graph, Claude Code, OpenAI AgentsJupyter Notebook, Knowledge Graph, Claude CodeClojure, Knowledge Graph, Claude CodePython, Knowledge Graph, Claude Code
WarningsNo OpenAgentSkill engagement data yetNo major risk signals from current metadataNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yet
Best forRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signalsRAG and knowledge 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
OpenAgentSkill engagement0 views
0 install copies
2 views
0 install copies
0 views
0 install copies
0 views
0 install copies
Install
$ npx skills add dylanhogg/llmgraph
$ npx skills add neo4j-labs/llm-graph-builder
$ npx skills add logseq/logseq
$ npx skills add OpenSPG/KAG