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by michelleoincx · Codex Skill · ★ 205

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

About zeroclaw-grok

ZeroClaw — sleek web interface for Grok AI (xAI). Streaming responses, multi-session chat, model selector. Zero npm dependencies. Runs with one command.

grokgrok-4grok-aigrok-apigrok-contextgrok-desktopgrok-desktop-appgrok-zeroclawgrok2grok3

Quick Facts

Stars205
Forks0
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score56.6354604538371/100
Last Updated2026-03-15
Created2026-03-14
Platformsbrowser, node
Est. Tokens~2k

Compatible Skills

These tools work well together with zeroclaw-grok for enhanced workflows:

  • Grok-MCP — semantic(0.43)+complementary+rare_topics+similar_pop (54%)

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Looking for a zeroclaw-grok alternative? If you're comparing zeroclaw-grok with other codex 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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Frequently Asked Questions

What is zeroclaw-grok?

zeroclaw-grok is ZeroClaw — sleek web interface for Grok AI (xAI). Streaming responses, multi-session chat, model selector. Zero npm dependencies. Runs with one command.. It is categorized as a Codex Skill with 205 GitHub stars.

What programming language is zeroclaw-grok written in?

zeroclaw-grok is primarily written in JavaScript. It covers topics such as grok, grok-4, grok-ai.

How do I install or use zeroclaw-grok?

You can find installation instructions and usage details in the zeroclaw-grok GitHub repository at github.com/michelleoincx/zeroclaw-grok. The project has 205 stars and 0 forks, indicating an active community.

What license does zeroclaw-grok use?

zeroclaw-grok is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to zeroclaw-grok?

The top alternatives to zeroclaw-grok on Agent Skills Hub include scira-mcp-chat, awesome-agent-skills, UnrealGenAISupport. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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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