awesome-japanese-nlp-resources: A curated list of resources for Japanese natural language processing

by taishi-i · Codex Skill · ★ 1.0k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install awesome-japanese-nlp-resources

/plugin marketplace add taishi-i/awesome-japanese-nlp-resources
git clone https://github.com/taishi-i/awesome-japanese-nlp-resources

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 59/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsawesomeawesome-listcc0japanesejapanese-languagellmnatural-language-processingnlpnlp-library

Quick Facts

Stars1,026
Forks59
CategoryCodex Skill
LicenseCC0-1.0
Quality Score59/100
Open Issues4
Last Updated2026-11-02
Created2022-06-08
Platformsclaude-code, codex
Est. Tokens~28k

About awesome-japanese-nlp-resources

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)...

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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