Skill audit report
MemoRizz: A Python library serving as a memory layer for AI applications. Leverages popular databases and storage solutions to optimize memory usage. Provides utility classes and methods for efficient data management.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
756 GitHub stars
Stars/forks activity
INFO71
756 stars, 77 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
PASS100
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS82
database surface
Install availability
PASS92
npx skills add RichmondAlake/memorizz
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO74
filesystem or document access, database access
Repository evidence
PASS86
https://github.com/RichmondAlake/memorizz
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add RichmondAlake/memorizz
Repository
88
https://github.com/RichmondAlake/memorizz
License
45
Unknown
Maintenance
88
2mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
100
Usable description available
Dependency risk
82
database surface
Install command safety
92
standard package or runtime install path
Permission surface
74
filesystem or document access, database access
Stars/forks activity
71
756 stars, 77 forks; issue activity unavailable in current metadata
Adoption
88
756 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
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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