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 taishi-i · Codex Skill · ★ 1.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-japanese-nlp-resources safe to install? View the security audit →
awesome-japanese-nlp-resources A curated list of resources dedicated to Python libraries, llms, dictionaries, and corpora of NLP for Japanese Listed information on 859 GitHub repositories Listed information on 364 Hugging Face repositories (models and datasets) 🎉 We are excited to announce the release of awesome-japanese-nlp-survey on March 1, 2026! English | [日本語 (Japanese) ](https://github.com/taishi-i/awesome-japanese-nlp-resources/
| Stars | 1,010 |
| Forks | 53 |
| Category | Codex Skill |
| License | CC0-1.0 |
| Quality Score | 59.3204802025043/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-21 |
| Created | 2022-06-08 |
| Platforms | claude-code, codex |
| Est. Tokens | ~28k |
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awesome-japanese-nlp-resources is A curated list of resources for Japanese natural language processing (NLP): Python libraries, LLMs, dictionaries, corpora, and datasets. Includes Claude Code and Codex skills to search resources.. It is categorized as a Codex Skill with 1.0k GitHub stars.
You can find installation instructions and usage details in the awesome-japanese-nlp-resources GitHub repository at github.com/taishi-i/awesome-japanese-nlp-resources. The project has 1.0k stars and 53 forks, indicating an active community.
awesome-japanese-nlp-resources is released under the CC0-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to awesome-japanese-nlp-resources on Agent Skills Hub include free-ai-resources-x, awesome-claude-skills, awesome-generative-ai. 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: