Skill audit report
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS86
1.4K GitHub stars
Stars/forks activity
INFO77
1.4K stars, 96 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
14d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS94
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO62
command execution surface, external package install surface
Install availability
PASS92
npx skills add OpenRaiser/NanoResearch --skill peft-fine-tuning
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO76
shell or command execution
Repository evidence
PASS86
https://github.com/OpenRaiser/NanoResearch/tree/main/skills/vendor-ai-research/peft
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add OpenRaiser/NanoResearch --skill peft-fine-tuning
Repository
88
https://github.com/OpenRaiser/NanoResearch/tree/main/skills/vendor-ai-research/peft
License
86
MIT
Maintenance
100
14d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
94
Usable description available
Dependency risk
62
command execution surface, external package install surface
Install command safety
92
standard package or runtime install path
Permission surface
76
shell or command execution
Stars/forks activity
77
1.4K stars, 96 forks; issue activity unavailable in current metadata
Adoption
88
1.4K 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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