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 askalf · Codex Skill · ★ 533
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is dario safe to install? View the security audit →
dario A local LLM router. One endpoint, every provider.Runs on your machine. Unifies OpenAI, Groq, OpenRouter, Ollama, vLLM, LiteLLM, any OpenAI-compat URL, and your Claude Max subscription (via OAuth) behind one endpoint at http://localhost:3456. Speaks both the Anthropic Messages API and the OpenAI Chat Completions API, so your tools stop caring which vendor is upstream. Drops in under the Claude Agent SDK as an API-key-compatible backend. Zero runtime dependencies. SLSA-attested on every release. Nothing phones home. Independent, unofficial, third-party — see DISCLAIMER.md. <img src="https://img.shields.io/npm/l/@askalf/dario"
| Stars | 533 |
| Forks | 65 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.8271096346494/100 |
| Open Issues | 8 |
| Last Updated | 2026-09-15 |
| Created | 2026-04-08 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~25k |
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dario is Use your Claude and ChatGPT subscriptions in Cursor, Cline, Aider, Claude Code and the Agent SDK — at subscription pricing, not per-token API bills. One local Anthropic + OpenAI-compatible endpoint: e. It is categorized as a Codex Skill with 533 GitHub stars.
dario is primarily written in JavaScript. It covers topics such as agent-sdk, ai-gateway, aider.
You can find installation instructions and usage details in the dario GitHub repository at github.com/askalf/dario. The project has 533 stars and 65 forks, indicating an active community.
dario is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to dario on Agent Skills Hub include ccproxy, holysheep-cli, octopus. 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: