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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

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Decision summary

Grasp MultiObject is the strongest overall pick here because it has a 32/100 readiness score and fits Coding agents.

Strongest overall

Grasp MultiObject

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

Fastest prototype

Grasp MultiObject

Best first install candidate based on install readiness and adoption.

Freshest repo

Grasp MultiObject

Most recent maintenance signal among this shortlist.

SignalGrasp MultiObject

Robotic grasp dataset for multi-object multi-grasp evaluation with RGB-D data. This dataset is annotated using the same protocal as Cornell Dataset, and can be used as multi-object extension of Cornell Dataset.

Quality
42/100
Needs review
Decision verdict
32/100
Needs manual review

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

Adoption114 stars
0 installs
FreshnessJul 28, 2020
Use-case fit
Coding agentsRAG and knowledgeWorkflow automation
Workflow fit
Content growth agentCoding review agent
Platform hintsMATLAB, Robotics, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
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OpenAgentSkill

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

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OpenAgentSkill Registry
PrivacyBuilt for agent-native discovery
Coding agents workflows · Claude Code teams · builders willing to evaluate younger projects
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add ivalab/grasp_multiObject