momo-code: RSI JEVPi --AI coding agent that evolves with you

by momozi1996 · Codex Skill · ★ 1.1k

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

How to install momo-code

git clone https://github.com/momozi1996/momo-code.git

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

Security audit verdict: SAFE · quality 71/100

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.

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Quick Facts

Stars1,106
Forks27
LanguageTypeScript
CategoryCodex Skill
Quality Score71/100
Last Updated2026-10-22
Created2026-06-16
Platformsclaude-code, cli, codex, node
Est. Tokens~22k

About momo-code

MOMO CODE AI-powered coding agent that evolves with you. Built on opencode with a unique dual-speed self-evolution system based on Pioneer Agent. ⚠️ Experimental / Active Development v2.0.0 (2026-10-11) 重大架构升级中。 当前版本引入了 Pi 框架集成、RSI 自进化循环和 JEV 决策层。 Pi 框架集成()作为扩展依赖 交互式 REPL,带思维链面板、决策胶囊与键盘快捷键 J

Compatible Skills

These tools work well together with momo-code for enhanced workflows:

  • container — semantic(0.29)+complementary+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • code-container — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • hippo-memory — semantic(0.15)+complementary+shared_fw(huggingface)+same_lang+similar_pop+shared_platform (63%)
  • Code-Agent-plusplus — semantic(0.40)+complementary+rare_topics+same_lang+shared_platform (63%)
  • opencode-mcp — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)

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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 Codex Skill tools