No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by HarnessMD · Codex Skill · ★ 8.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is munder-difflin safe to install? View the security audit →
Munder Difflin Agent harness to run an office of your clones Free, open source and performant. A multi-agent harness that works with the subscriptions you already pay for, on their hourly limits. It turns the terminal coding CLI you already run into a clone of you, one that keeps working while you're away and coordinates a whole office of agents on your own machine. Wraps Claude Code, Antigravity (Gemini), OpenAI Codex, xAI Grok, Kimi Code, Gemini CLI, Qwen, OpenCode,
| Stars | 8,367 |
| Forks | 1,123 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63.6119894444915/100 |
| Open Issues | 223 |
| Last Updated | 2026-10-03 |
| Created | 2026-05-31 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~22k |
These tools work well together with munder-difflin for enhanced workflows:
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munder-difflin is an open-source alternative to the dots, bots and muses of the world, run an office of claude code/codex like agents on your laptop, sandboxes or anywhere, uses your existing subscriptions. It is categorized as a Codex Skill with 8.4k GitHub stars.
munder-difflin is primarily written in TypeScript. It covers topics such as agent-harness, agent-orchestration, agents.
You can find installation instructions and usage details in the munder-difflin GitHub repository at github.com/HarnessMD/munder-difflin. The project has 8.4k stars and 1123 forks, indicating an active community.
munder-difflin is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to munder-difflin on Agent Skills Hub include superset, holaOS, awesome-agent-orchestrators. 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: