Skill audit report
Design, index, query, and tune Lance datasets and LanceDB tables for ML and AI workloads. Use for vector index selection such as IVF_PQ or IVF_HNSW_FLAT, ANN recall and latency tuning, full-text and hybrid search, scalar indexes and prefiltering, dataset versioning and compaction, embedding and multimodal storage, slow vector search on object storage, or migrating ML data from Parquet. Covers both the pylance format and the lancedb API.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
38 GitHub stars
Stars/forks activity
WARN43
38 stars, 4 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN56
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add gordonmurray/data-engineering-skills --skill lance
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL34
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/gordonmurray/data-engineering-skills/tree/main/lance
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add gordonmurray/data-engineering-skills --skill lance
Repository
88
https://github.com/gordonmurray/data-engineering-skills/tree/main/lance
License
86
MIT
Maintenance
88
2mo since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
56
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
34
secrets or environment access, filesystem or document access
Stars/forks activity
43
38 stars, 4 forks; issue activity unavailable in current metadata
Adoption
42
38 GitHub stars
Warnings
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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