Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by doramirdor · Claude Skill · ★ 336
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is NadirClaw safe to install? View the security audit →
NadirClaw Your simple prompts are burning premium tokens. NadirClaw routes them to cheaper models automatically. Save 40-70% on AI API costs. Works with Claude Code · Cursor · Continue · Aider · Windsurf · Codex · OpenClaw · Open WebUI · Any OpenAI-compatible client Website · Quick Start · <a href="docs/compa
| Stars | 336 |
| Forks | 44 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 76.4742185246205/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-20 |
| Created | 2026-02-11 |
| Platforms | claude-code, codex, gemini, python |
| Est. Tokens | ~161k |
Looking for a NadirClaw alternative? If you're comparing NadirClaw with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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NadirClaw is Open-source LLM router & AI cost optimizer. Routes simple prompts to cheap/local models, complex ones to premium — automatically. Drop-in OpenAI-compatible proxy for Claude Code, Codex, Cursor, OpenCl. It is categorized as a Claude Skill with 336 GitHub stars.
NadirClaw is primarily written in Python. It covers topics such as ai, ai-cost-reduction, ai-router.
You can find installation instructions and usage details in the NadirClaw GitHub repository at github.com/doramirdor/NadirClaw. The project has 336 stars and 44 forks, indicating an active community.
NadirClaw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to NadirClaw on Agent Skills Hub include NadirClaw, ccproxy, SimplerLLM. 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: