Codync: The open-source Grok Bot alternative: message Claude Code, Codex, Cursor, Gemini and 40+ AI agents as bots

by leepokai · Codex Skill · ★ 737

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

How to install Codync

brew install --cask leepokai/codync/codync

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.

acpagent-client-protocolai-agentsclaudeclaude-codecodexcoding-agentscursorelectrongemini

Quick Facts

Stars737
Forks91
LanguageRust
CategoryCodex Skill
LicenseApache-2.0
Quality Score65/100
Open Issues32
Last Updated2026-10-22
Created2026-03-18
Platformsclaude-code, cli, codex, gemini, rust
Est. Tokens~24k

About Codync

Codync The open-source, 1:1 alternative to Grok Bot and Muse. Your coding agents, as teammates you can message. Codync turns the coding agents on your computer — Claude Code, Codex, Cursor, Pi, OpenCode, Grok Build, Gemini, Copilot and 40 more — into persistent bots you delegate to from your iPhone, Mac, Linux desktop or any terminal, the way you'd message a colleague.

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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 Codex Skill tools