deepseek-whalechan: Keep Whale-chan consistently vivid in every generation: High-consistency character design specification

by Neko3000 · Codex Skill · ★ 474

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

How to install deepseek-whalechan

git clone https://github.com/Neko3000/deepseek-whalechan.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 58/100

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.

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.

claude-codecodexcomicsgeminigraphicsskills

Quick Facts

Stars474
Forks20
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score58/100
Open Issues3
Last Updated2026-10-27
Created2026-08-22
Platformsclaude-code, codex, gemini, python
Est. Tokens~20k

About deepseek-whalechan

DeepSeek Whale-chan · 深度求索 鲸鱼娘 Keep Whale-chan consistently vivid in every generation: High-consistency character design specification, visual asset library, and agent creation suite 简体中文 日本語 Table of Contents [Project Overview](#-project-overvi

Compatible Skills

These tools work well together with deepseek-whalechan for enhanced workflows:

  • skills — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)
  • SkillForge — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)

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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:

View on GitHub → Browse Codex Skill tools