Skill audit report
SQLCell is a magic function for the Jupyter Notebook that executes raw, parallel, parameterized SQL queries with the ability to accept Python values as parameters and assign output data to Python variables while concurrently running Python code. And *much* more.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
150 GitHub stars
Stars/forks activity
WARN57
150 stars, 11 forks; issue activity unavailable in current metadata
Recent maintenance
FAIL22
4y since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS82
database surface
Install availability
PASS92
npx skills add tmthyjames/SQLCell
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/tmthyjames/SQLCell
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add tmthyjames/SQLCell
Repository
88
https://github.com/tmthyjames/SQLCell
License
86
MIT
Maintenance
20
4y since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
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
57
150 stars, 11 forks; issue activity unavailable in current metadata
Adoption
68
150 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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