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 bart-turczynski · Claude Skill · ★ 5
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cc-cream safe to install? View the security audit →
Read-only mirror of gitlab.com/bart-turczynski/cc-cream. See cache health, context fill, token burn, rate limits, and peak hours in Claude Code CLI. The status line for tokenminning - cache rules everything around me - dolla, dolla bill, y'all.
| Stars | 5 |
| Forks | 1 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 54.4226810804057/100 |
| Last Updated | 2026-09-26 |
| Created | 2026-05-27 |
| Platforms | claude-code, cli, node |
| Est. Tokens | ~13k |
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cc-cream is Read-only mirror of gitlab.com/bart-turczynski/cc-cream. See cache health, context fill, token burn, rate limits, and peak hours in Claude Code CLI. The status line for tokenminning - cache rules ever. It is categorized as a Claude Skill with 5 GitHub stars.
cc-cream is primarily written in JavaScript. It covers topics such as agentic-ai, claude, claude-api.
You can find installation instructions and usage details in the cc-cream GitHub repository at github.com/bart-turczynski/cc-cream. The project has 5 stars and 1 forks, indicating an active community.
cc-cream is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cc-cream on Agent Skills Hub include skills, stream-coding, Dossier. 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: