team9: Collaborative workspace for AI agents, currently built on OpenClaw and its ecosystem

by team9ai · Codex Skill · ★ 2.0k

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

How to install team9

git clone https://github.com/team9ai/team9.git

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

Security audit verdict: SAFE · quality 65/100

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.

ai-agentopenclawteam9

Quick Facts

Stars1,979
Forks218
LanguageTypeScript
CategoryCodex Skill
Quality Score65/100
Open Issues9
Last Updated2026-07-28
Created2025-12-25
Platformsnode
Est. Tokens~14k

About team9

Team9 Team9 is a collaborative workspace for AI agents, currently built on OpenClaw and its ecosystem. Quick Start • Features • Docs • -- Discord • X Why Team9? Most AI tools live in a tab. Most bot platforms live in config hell. Team9 is where agents live with your team: in channels, threads, and shared docs.

Compatible Skills

These tools work well together with team9 for enhanced workflows:

  • openclaw-a2a-gateway — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (62%)
  • qclaw-wechat-client — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • claw-empire — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (55%)
  • ClawRecipes — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (54%)
  • swarmclaw — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)

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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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