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NVIDIA/SkillSpector

Establishedrank #86

Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.

18.5k+1.3k · 7d 1.6k 108est. Apache-2.0Pythonpushed 5m ago
Compare View on GitHub

Composite

72

conf 65%

Momentum

68

conf 60%

Vitality (PVI)

71

conf 67%

Community

68

conf 60%

Security & maint.

89

conf 85%

Ecosystem influence

67

conf 60%

Opportunity

70

conf 60%

Breakout · 7d

38%

conf 71%

Executive summary

SkillSpector is currently classified as established with a composite score of 72/100. Momentum (68) and vitality (71) are aligned — growth is backed by sustained maintenance. Estimated 7-day gain of 1,254 stars against a 18.5k-star base. Risk is assessed as low; the interpretable model puts its probability of entering the top trend cohort within 7 days at 38%.

90-day trajectory

+6.3k · 30d
2026-07-012026-09-28

Score breakdown

Every input, weight and normalized value — nothing hidden. Inputs marked est. are estimated until the full ingestion pipeline lands.

Momentum

Star velocityest.25%86
Star accelerationest.15%43
Fork velocityest.10%84
Contributor growthest.10%77
Issue activity growthest.10%75
PR activity growthest.10%48
External mention velocityest.10%65
Release event impactest.5%67
Trending-rank persistenceest.5%39

Model tn-interpretable-1.0.0 · confidence 60% · coverage 100%

Project Vitality Index

Commit consistency20%100
Release cadenceest.15%65
PR responsivenessest.15%55
Issue responsivenessest.15%62
Contributor diversityest.10%75
Maintainer continuityest.10%74
Documentation qualityest.5%73
Dependency freshnessest.5%68
Security hygieneest.5%37

Model tn-interpretable-1.0.0 · confidence 67% · coverage 100%

Security & maintenance

Release recency25%100
License clarity20%92
Maintenance status25%100
Dependency stalenessest.15%63
Bus factorest.15%77

Model tn-interpretable-1.0.0 · confidence 85% · coverage 100%

Ecosystem influence

Dependent repositoriesest.30%80
Quality-weighted dependentsest.20%67
Documentation citationsest.15%64
Contributor overlapest.15%49
Registry adoptionest.10%29
Topic centralityest.10%100

Model tn-interpretable-1.0.0 · confidence 60% · coverage 92% · missing: packageRegistryAdoption