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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 1 skill

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

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Decision summary

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

Strongest overall

Memsearch

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

Fastest prototype

Memsearch

Best first install candidate based on install readiness and adoption.

Freshest repo

Memsearch

Most recent maintenance signal among this shortlist.

SignalMemsearch

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex), backed by Markdown and Milvus.

Quality
100/100
Excellent
Decision verdict
100/100
Production-ready

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

Adoption2.1K stars
0 installs
FreshnessJun 18, 2026
Use-case fit
RAG and knowledgeCoding agentsSports analytics
Stack fit
RAG knowledge baseCoding review agent
Platform hintsPython, Semantic Search, Claude Code, OpenAI Agents
WarningsNo major risk signals from current metadata
Best forRAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signals
OpenAgentSkill

The skill layer for AI agents: discover, compare, audit, and install reusable capabilities across Codex, Claude Code, Cursor, and agent runtimes.

GitHubX

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DocsAbout OpenAgentSkillAPIllms.txtOpenAPICLICreator KitX Growth KitSubmitBlogGuidesActivity
OpenAgentSkill Registry
PrivacyBuilt for agent-native discovery
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security review
OpenAgentSkill engagement5 views
0 install copies
Install
$ npx skills add zilliztech/memsearch