OpenMythos: A theoretical reconstruction of the Claude Mythos architecture, built from first principles

by kyegomez · Claude Skill · ★ 14.9k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install OpenMythos

pip install open-mythos

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aianthropicattentionclaudeclaude-aiclaude-codeclaude-code-pluginclaude-mythosclaude-sonnetdeepmind

Quick Facts

Stars14,902
Forks3,296
LanguagePython
CategoryClaude Skill
LicenseMIT
Quality Score69/100
Open Issues61
Last Updated2026-05-23
Created2026-04-18
Platformsclaude-code, python
Est. Tokens~8k

About OpenMythos

OpenMythos Disclaimer: OpenMythos is an independent, community-driven theoretical reconstruction based solely on publicly available research and speculation. It is not affiliated with, endorsed by, or connected to Anthropic or any of their proprietary systems. OpenMythos is an open-source, theoretical implementation of the Claude Mythos model.

Compatible Skills

These tools work well together with OpenMythos for enhanced workflows:

  • claude-code-gpt-5-codex — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • superml — semantic(0.15)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • 3dsmax-mcp — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (57%)
  • claude-prompt-engineering-guide — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (57%)
  • py-gpt — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)

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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:

View on GitHub → Browse Claude Skill tools