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 nghyane · Codex Skill · ★ 330
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is launchdock safe to install? View the security audit →
launchdock Use Claude and GPT across AI coding tools through one local gateway, with both OpenAI-compatible and Claude-native API surfaces. gives you one local endpoint for tools like OpenCode, Codex, Claude Code, Droid, and Pi. Why people use it: use OpenCode or Codex with the accounts you already have use Claude through either OpenAI-compatible chat clients or the native Claude Messages API avoid managing separate credentials and configs everywhere log in once and reuse managed auth across multiple tools push managed auth to a personal server when needed Install Optional: Quickstart bash launchdock auth login claude launchdock auth login openai launchdock auth list launchdock start laun
| Stars | 330 |
| Forks | 93 |
| Language | Go |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 69.5864181543589/100 |
| Open Issues | 9 |
| Last Updated | 2026-05-01 |
| Created | 2025-12-09 |
| Platforms | claude-code, codex, go |
| Est. Tokens | ~4674k |
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launchdock is Use Claude and GPT through one local gateway with OpenAI-compatible and Claude-native APIs.. It is categorized as a Codex Skill with 330 GitHub stars.
launchdock is primarily written in Go. It covers topics such as ai-tools, anthropic, claude.
You can find installation instructions and usage details in the launchdock GitHub repository at github.com/nghyane/launchdock. The project has 330 stars and 93 forks, indicating an active community.
launchdock is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to launchdock on Agent Skills Hub include ocp, claude-delegator, UnrealClaude. 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: