Skill comparison
Compare agent skills before installing.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
AI For Beginners is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
AI For Beginners
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
AI For Beginners
Best first install candidate based on install readiness and adoption.
Freshest repo
Xgboost
Most recent maintenance signal among this shortlist.
| Signal | DOOR SLAM Distributed, Online, and Outlier Resilient SLAM for Robotic Teams | Conductor Conductor is an event driven agentic workflow engine providing durable and highly resilient execution engine for applications and AI Agents | Xgboost Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow | AI For Beginners 12 Weeks, 24 Lessons, AI for All! |
|---|---|---|---|---|
| Quality | 50/100 Needs review | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 40/100 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. |
| Adoption | 249 stars 0 installs | 32K stars 0 installs | 28K stars 0 installs | 48K stars 0 installs |
| Freshness | Mar 14, 2023 | Jun 13, 2026 | Jun 16, 2026 | Jun 11, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Dockerfile, Computer Vision, Claude Code | Java, Workflow, Claude Code | C++, Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Local desktop workflows · Claude Code teams · builders willing to evaluate younger projects | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Sports analytics workflows · Claude Code teams · teams that value GitHub adoption signals | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that require actively maintained dependencies · production agents without a repository review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add MISTLab/DOOR-SLAM | $ npx skills add conductor-oss/conductor | $ npx skills add dmlc/xgboost | $ npx skills add microsoft/AI-For-Beginners |