Skill audit report
Retrieve and update scoped AutoBot memory and apply user corrections with provenance. Use when the user asks to remember a durable fact, correct a saved preference or carry a lesson into later work.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
FAIL30
21 GitHub stars
Stars/forks activity
FAIL32
21 stars, 1 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
4d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN46
command execution surface, credential or environment access
Install availability
PASS92
npx skills add demeyer1/Autobot --skill remember-and-improve
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL24
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/demeyer1/Autobot/tree/main/skills/remember-and-improve
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add demeyer1/Autobot --skill remember-and-improve
Repository
88
https://github.com/demeyer1/Autobot/tree/main/skills/remember-and-improve
License
86
MIT
Maintenance
100
4d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
46
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
24
secrets or environment access, shell or command execution
Stars/forks activity
32
21 stars, 1 forks; issue activity unavailable in current metadata
Adoption
42
21 GitHub stars
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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