cavemem: Frozen — cross-agent persistent memory for coding assistants

by JuliusBrussee · Claude Skill · ★ 675

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

How to install cavemem

npm install -g cavemem

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

Security audit verdict: SAFE · quality 74/100

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

Stars675
Forks58
LanguageTypeScript
CategoryClaude Skill
LicenseMIT
Quality Score74/100
Open Issues12
Last Updated2026-08-14
Created2026-04-18
Platformsclaude-code, node
Est. Tokens~15k

About cavemem

cavemem why agent forget when agent can remember Install • How it works • CLI • MCP • Settings 🪨 Caveman Ecosystem  ·  caveman talk less  ·  cavemem remember more (you are here)  ·  cavekit build better Cross-agent persistent memory for coding assistants.

Compatible Skills

These tools work well together with cavemem for enhanced workflows:

  • Ori-Mnemos — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)
  • DeepWideResearch — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • cortex-hub — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • codemem — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (55%)

cavemem alternative? Top 6 similar tools

Looking for a cavemem alternative? If you're comparing cavemem with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • Grov by TonyStef · ⭐ 192

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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