Skill audit report
Intake for an autonomous research run (Arbor). Use when the user wants to optimize a metric in a repo over many isolated experiments — 'optimize this benchmark', 'improve the model F1 overnight', 'beat the leaderboard'. Discovers the repo/eval/splits, measures the baseline, confirms a Research Contract, then emits a ready-to-send /auto-research command. Does NOT start the run itself.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
25 GitHub stars
Stars/forks activity
WARN43
25 stars, 1 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
21d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS94
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO72
credential or environment access
Install availability
PASS92
npx skills add invergent-ai/surogates --skill arbor-research
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL36
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/invergent-ai/surogates/tree/master/skills/research/arbor-research
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add invergent-ai/surogates --skill arbor-research
Repository
88
https://github.com/invergent-ai/surogates/tree/master/skills/research/arbor-research
License
86
MIT
Maintenance
100
21d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
94
Usable description available
Dependency risk
72
credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
36
secrets or environment access, shell or command execution
Stars/forks activity
43
25 stars, 1 forks; issue activity unavailable in current metadata
Adoption
42
25 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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