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 0-to-1-Labs · Claude Skill · ★ 47
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-code-prompt-optimizer safe to install? View the security audit →
AI-powered prompt optimization hook for Claude Code. Transforms simple prompts into comprehensive, structured instructions using Claude Opus 4.6's advanced reasoning capabilities.
| Stars | 47 |
| Forks | 4 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 73.2178822209519/100 |
| Last Updated | 2026-09-30 |
| Created | 2025-10-09 |
| Platforms | claude-code, node |
| Est. Tokens | ~17k |
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claude-code-prompt-optimizer is AI-powered prompt optimization hook for Claude Code. Transforms simple prompts into comprehensive, structured instructions using Claude Opus 4.6's advanced reasoning capabilities.. It is categorized as a Claude Skill with 47 GitHub stars.
claude-code-prompt-optimizer is primarily written in TypeScript. It covers topics such as ai, anthropic, claude.
You can find installation instructions and usage details in the claude-code-prompt-optimizer GitHub repository at github.com/0-to-1-Labs/claude-code-prompt-optimizer. The project has 47 stars and 4 forks, indicating an active community.
claude-code-prompt-optimizer is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-code-prompt-optimizer on Agent Skills Hub include claude-emporium, palot, claude-historian-mcp. 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: