Skill audit report
QuantLib SWIG audit report.
QuantLib wrappers to other languages
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, install safety, permission surface, 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
INFO62
393 GitHub stars
Stars/forks activity
INFO68
393 stars, 319 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
6d since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add lballabio/QuantLib-SWIG
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/lballabio/QuantLib-SWIG
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add lballabio/QuantLib-SWIG
Repository
88
https://github.com/lballabio/QuantLib-SWIG
License
45
Unknown
Maintenance
100
6d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
84
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
68
393 stars, 319 forks; issue activity unavailable in current metadata
Adoption
68
393 GitHub stars
Warnings
- License is unclear
- Quality score needs review
- License clarity: Unknown
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.
Compare nearby options