Skill audit report
Lance audit report.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, dependency risk, and installability.
The Trust Score is OpenAgentSkill's adoption layer. It is designed to help an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS94
6.7K GitHub stars
Recent maintenance
PASS100
1d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add lance-format/lance
Repository evidence
PASS86
https://github.com/lance-format/lance
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add lance-format/lance
Repository
88
https://github.com/lance-format/lance
License
86
Apache-2.0
Maintenance
100
1d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Adoption
88
6.7K GitHub stars
Warnings
No major warnings detected from available metadata.
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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