Skill audit report
Author and optionally direct-launch a two-node loop-graph run that compares feasible technical approaches with open-source evidence, primary research, and controlled experiments before selecting one. Use when a decision needs several research and evaluation rounds with durable evidence and independent audit. Not for implementing an already chosen requirement, code cleanup, or a quick literature summary. Do not execute or resume generated runtime node files from this authoring skill.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
76 GitHub stars
Stars/forks activity
WARN43
76 stars, 9 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
12d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add levi-qiao/longgraph-skill --skill loop-research
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/levi-qiao/longgraph-skill/tree/main/skills/loop-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 levi-qiao/longgraph-skill --skill loop-research
Repository
88
https://github.com/levi-qiao/longgraph-skill/tree/main/skills/loop-research
License
86
MIT
Maintenance
100
12d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
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
43
76 stars, 9 forks; issue activity unavailable in current metadata
Adoption
68
76 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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