Skill audit report
Neo4j Python Pandas Py2neo V3 audit report.
Excel-to-Neo4j knowledge graph examples: legacy py2neo v3 plus modern Neo4j GraphRAG/vector search.
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
INFO76
579 GitHub stars
Recent maintenance
PASS100
3d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS100
Metadata includes enough usage and workflow context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add MazzaWill/neo4j-python-pandas-py2neo-v3
Repository evidence
PASS86
https://github.com/MazzaWill/neo4j-python-pandas-py2neo-v3
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add MazzaWill/neo4j-python-pandas-py2neo-v3
Repository
88
https://github.com/MazzaWill/neo4j-python-pandas-py2neo-v3
License
86
MIT
Maintenance
100
3d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
100
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Adoption
88
579 GitHub stars
Warnings
- Quality score needs review
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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