matrix-core: Matrix by PaxLabs is a production-grade framework for building autonomous AI agents that go beyond chat

by paxlabs-inc · Agent Tool · ★ 164

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

Security audit verdict: SAFE · quality 53/100

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.

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.

agentic-aiagentsaiartificial-neural-networksautomationautonomous-agentsexpert-agentsmatrixnatural-language-processingneocortex

Quick Facts

Stars164
Forks12
LanguageGo
CategoryAgent Tool
Quality Score53/100
Open Issues14
Last Updated2026-08-11
Created2026-06-05
Platformsbrowser, go
Est. Tokens~15k

About matrix-core

A stateful AI operating system for serious, long-horizon work. [!IMPORTANT] THIS REPOSITORY IS NOW ARCHIVED, CENTRA'S NEW GEN AGENTS ARE IN sidiora-labs/centra-gideon-agent Centra AI gives agents memory, tools, isolated computers, coordinated work, and a durable record of what they actually did. License FAQ Q: Can I use Centra AI for free? Yes.

Compatible Skills

These tools work well together with matrix-core for enhanced workflows:

  • AgenticGoKit — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (57%)
  • pgmcp — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • pls — semantic(0.33)+complementary+rare_topics+similar_pop (51%)

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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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