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NVIDIA/SkillSpector

SkillSpector scans agent skills for security risks before installation, with static checks, optional LLM analysis, and reports that can feed CI. Its cited research subset found vulnerabilities in 26.1% of skills.

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Source Summary

SkillSpector checks skills from repositories, URLs, archives, directories, or files using **71 vulnerability patterns across 17 categories**. It combines static analysis with optional LLM review and can emit SARIF, JSON, Markdown, or terminal reports. The cited dataset subset contained 31,132 skills; **26.1% had vulnerabilities** and 5.2% showed likely malicious intent. Add a scan before installing third-party skills, or use SARIF and `--fail-on-incomplete` to support CI gates. Baselines can suppress findings already reviewed so later scans surface new ones. A scanner report is a review aid, not proof a skill is safe. Findings can be suppressed, and caller exclusions make coverage partial and prevent a SAFE recommendation. LLM analysis is optional and requires provider configuration.

Practical Implication

No separate implication has been recorded yet.

Agent-Ready Context
SkillSpector checks skills from repositories, URLs, archives, directories, or files using **71 vulnerability patterns across 17 categories**. It combines static analysis with optional LLM review and can emit SARIF, JSON, Markdown, or terminal reports. The cited dataset subset contained 31,132 skills; **26.1% had vulnerabilities** and 5.2% showed likely malicious intent.
Add a scan before installing third-party skills, or use SARIF and `--fail-on-incomplete` to support CI gates. Baselines can suppress findings already reviewed so later scans surface new ones.
A scanner report is a review aid, not proof a skill is safe. Findings can be suppressed, and caller exclusions make coverage partial and prevent a SAFE recommendation. LLM analysis is optional and requires provider configuration.
Connected Context · Feed7 Judgment

This makes third-party skill review a repeatable scanning step, with CI output and baselines to track newly surfaced findings. Its dataset figures give scale to the exposure concern, while the caveats matter operationally: a clean report is not a safety guarantee, and exclusions can leave coverage incomplete.

We Vetted 2000 AI Skills Before They Reached Developers — Lucas Palma, NubankBoth treat skills as supply-chain dependencies and describe scanning in operational workflows; SkillSpector adds concrete scan inputs, report formats, baselines, and an explicit limit on what a clean result proves.anthropics/claude-plugins-communityThe reviewed plugin mirror screens entries before distribution, while SkillSpector offers a scanner teams can use for their own review; scanning alone does not establish the mirror's unspecified review criteria or behavioral guarantees.VoltAgent/awesome-agent-skillsThe discovery index makes selective adoption important, and SkillSpector supplies a way to inspect candidate skills before installing them; neither catalog inclusion nor scan results replace broader evaluation.zhaoxuya520/reverse-skillThe security router's broad skill-pack concern is directly addressed by independent scanning, while its authorization and evidence workflow covers risks a static or optional LLM scan cannot resolve.
Context Map
toolscodingsecurity#skills#tool-use