by AbhishekK130804 · Claude Skill · ★ 231
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Claude pro free Mythos design Opus Cowork Sonnet AI Anthropic App: download free PC android apk iOS, Anthropic Claude API key setup, Claude roleplay mythos client, SillyTavern Claude prompt formatting, custom system prompt jailbreak, Mythos AI creative writing app, Claude 3.5 Sonnet Opus API cost, open source LLM frontend, Claude reverse proxy
| Stars | 231 |
| Forks | 0 |
| Language | C# |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 54.2421283835822/100 |
| Last Updated | 2026-05-18 |
| Created | 2026-05-18 |
| Platforms | claude-code, cli, dotnet |
| Est. Tokens | ~15k |
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Claude-Mythos-AI-Anthropic-App is Claude pro free Mythos design Opus Cowork Sonnet AI Anthropic App: download free PC android apk iOS, Anthropic Claude API key setup, Claude roleplay mythos client, SillyTavern Claude prompt formattin. It is categorized as a Claude Skill with 231 GitHub stars.
Claude-Mythos-AI-Anthropic-App is primarily written in C#. It covers topics such as claude, claude-ai, claude-code.
You can find installation instructions and usage details in the Claude-Mythos-AI-Anthropic-App GitHub repository at github.com/AbhishekK130804/Claude-Mythos-AI-Anthropic-App. The project has 231 stars and 0 forks, indicating an active community.
Claude-Mythos-AI-Anthropic-App is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Claude-Mythos-AI-Anthropic-App on Agent Skills Hub include Themata-Claude-Scribe, Mythos-Claude-Orchestrator, Claude-Code-Design-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: