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 lfnovo · Agent Tool · ★ 212
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is esperanto safe to install? View the security audit →
Esperanto 🌐 Esperanto is a powerful Python library that provides a unified interface for interacting with various Large Language Model (LLM) providers. It simplifies the process of working with different AI models (LLMs, Embedders, Transcribers, and TTS) APIs by offering a consistent interface while maintaining provider-specific optimizations. Why Esperanto? 🚀 🪶 Ultra-Lightweight Architecture Direct HTTP Communication: All providers communicate directly via HTTP APIs using - no bulky vendor SDKs required Minimal Dependencies: Unlike LangChain and similar frameworks, Esperanto has a tiny footprint with zero overhead layers Production-Ready Performance: Direct API calls mean faster response times and lower memory usage 🔄 True Provider Flexibility Standardized Responses: Switch between any provider (OpenAI ↔ Anthropic ↔ Google ↔ etc.) without changing a single line of code Consistent Interface: Same methods, same
| Stars | 212 |
| Forks | 49 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.6470045334137/100 |
| Open Issues | 28 |
| Last Updated | 2026-09-05 |
| Created | 2024-11-23 |
| Platforms | gemini, python |
| Est. Tokens | ~21k |
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esperanto is A unified interface for various AI model providers. It is categorized as a Agent Tool with 212 GitHub stars.
esperanto is primarily written in Python. It covers topics such as anthropic, embeddings, gemini.
You can find installation instructions and usage details in the esperanto GitHub repository at github.com/lfnovo/esperanto. The project has 212 stars and 49 forks, indicating an active community.
esperanto is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to esperanto on Agent Skills Hub include vllora, SimplerLLM, InferrLM. 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: