by snarktank · Codex Skill · ★ 2.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Build your agent team in OpenClaw with one command.
| Stars | 2,499 |
| Forks | 453 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 49.0269869255681/100 |
| Open Issues | 113 |
| Last Updated | 2026-02-26 |
| Created | 2026-02-06 |
| Platforms | node |
| Est. Tokens | ~13k |
These tools work well together with antfarm for enhanced workflows:
Looking for a antfarm alternative? If you're comparing antfarm 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.
The first open-source agent skills builder. Define skills by vibe workflow, run on Claude Code, Cursor, Codex
Bridge Claude Code / Codex to IM platforms — chat with AI coding agents from Telegram, Discord, or Feishu/Lark
📚 Sync skills across all AI CLI tools with one command and simplify team sharing. Supporting Codex, Claude Co
Build tested agent skills and govern their lifecycle through a user-defined marketplace: evidence, discovery,
A Claude or Codex skill for deliberate skill development during AI-assisted coding
Skills for pi coding agent (compatible with Claude Code and Codex CLI)
Explore other popular codex skill tools:
antfarm is Build your agent team in OpenClaw with one command.. It is categorized as a Codex Skill with 2.5k GitHub stars.
antfarm is primarily written in TypeScript.
You can find installation instructions and usage details in the antfarm GitHub repository at github.com/snarktank/antfarm. The project has 2.5k stars and 453 forks, indicating an active community.
antfarm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to antfarm on Agent Skills Hub include refly, Claude-to-IM-skill, skillshare. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: