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 OpenRouterTeam · Agent Tool · ★ 367
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openrouter-examples safe to install? View the security audit →
OpenRouter Examples Comprehensive, tested, executable examples demonstrating OpenRouter features across multiple ecosystems. Quick Start Repository Structure Features Prompt Caching Documentation: docs/prompt-caching.md Examples: curl/prompt-caching.sh typescript/fetch/src/prompt-caching/ typescript/ai-sdk-v5/src/prompt-caching/ typescript/effect-ai/src/prompt-caching/ Prerequisites Bun runtime: OpenRouter API key: https://openrouter.ai/keys For curl examples: (JSON processor)
| Stars | 367 |
| Forks | 73 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.1067869249981/100 |
| Open Issues | 29 |
| Last Updated | 2026-03-30 |
| Created | 2023-07-14 |
| Platforms | node |
| Est. Tokens | ~2173k |
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openrouter-examples is Examples of integrating the OpenRouter API. It is categorized as a Agent Tool with 367 GitHub stars.
openrouter-examples is primarily written in TypeScript. It covers topics such as ai, anthropic, docs.
You can find installation instructions and usage details in the openrouter-examples GitHub repository at github.com/OpenRouterTeam/openrouter-examples. The project has 367 stars and 73 forks, indicating an active community.
openrouter-examples is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openrouter-examples on Agent Skills Hub include ccproxy, SimplerLLM, kea-research. 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: