Claude-Mythos-AI-Anthropic-App — repository deleted, archived audit

Quick Facts

About Claude-Mythos-AI-Anthropic-App

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Compatible Skills

These tools work well together with Claude-Mythos-AI-Anthropic-App for enhanced workflows:

• mythos-router — semantic(0.39)+complementary+shared_fw(anthropic)+rare_topics+similar_pop+shared_platform (75%)
• Claude-Zeroclaw — semantic(0.37)+complementary+shared_fw(anthropic)+rare_topics+similar_pop+shared_platform (66%)
• Claude-Code-Design-AI — semantic(0.70)+rare_topics+similar_pop+shared_platform (60%)
• nWave — semantic(0.30)+complementary+rare_topics+similar_pop+shared_platform (59%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this