Skill audit report
RAG With Amazon Bedrock And Pgvector Audit report.
Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)
OpenAgentSkill Trust Score
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
102 GitHub stars
Stars/forks activity
WARN57
102 stars, 18 forks; issue activity unavailable in current metadata
Recent maintenance
INFO62
11mo since push
License clarity
PASS86
MIT-0
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO80
external package install surface
Install availability
PASS92
npx skills add aws-samples/rag-with-amazon-bedrock-and-pgvector
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/aws-samples/rag-with-amazon-bedrock-and-pgvector
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install and adoption review
Install path
92
npx skills add aws-samples/rag-with-amazon-bedrock-and-pgvector
Repository
88
https://github.com/aws-samples/rag-with-amazon-bedrock-and-pgvector
License
86
MIT-0
Maintenance
62
11mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
80
external package install surface
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
57
102 stars, 18 forks; issue activity unavailable in current metadata
Adoption
68
102 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
- Financial research output is not financial advice; require human review before any live investment decision
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Stars/forks activity: 102 stars, 18 forks; issue activity unavailable in current 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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