Avernet: Distributed agent coordination platform where agents live, connect, coordinate, execute, and evolve together

by inclusionAI · Codex Skill · ★ 593

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

How to install Avernet

git clone https://github.com/inclusionAI/Avernet.git

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

Security audit verdict: SAFE · quality 48/100

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.

agent-coordinationagent-infrastructureagent-networkagent-orgnaizationai-agentsdistributed-systemsmulti-agentopenclawpythonrust

Quick Facts

Stars593
Forks66
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score48/100
Open Issues168
Last Updated2026-10-26
Created2026-07-06
Platformspython
Est. Tokens~13k

About Avernet

Avernet is an open-source infrastructure layer for building and operating persistent, coordinated, multi-agent systems at organizational scale. Where agents live, connect, coordinate, execute, and evolve together.

Compatible Skills

These tools work well together with Avernet for enhanced workflows:

  • nelson — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • nelson — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)

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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:

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