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 e10nMa2k · Agent Tool · ★ 962
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cc-mini safe to install? View the security audit →
cc-mini Ultra-light Harness scaffolding for AI agents Agentic · Built to Extend · From Claude Code The entire core is NEW: Buddy — AI Companion with Custom Sprites Your coding companion lives in the terminal. Type to hatch it. Supports custom ASCII species — bring your own Pikachu! Full Buddy docs → Features Core Interactive REPL with streaming output, command history, slash command autocomplete Agentic tool loop — Claude calls tools autonomously until the task is complete 9 built-in tools: , , , , , , , , Plan mode — parallel subagents explore codebase before you implement, with permission isolation Permission system — mode-aware (default/plan), reads auto-approved, writes/bash ask for confirmation Session persistence — auto-save conversations, to continue later Context compression — auto-compact when approaching token limits Anthropic + OpenAI compatible — works with any compatible API endpoint Advanced (from unreleased Claude Code features) [docs →](docs/c
| Stars | 962 |
| Forks | 357 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 69.9982193483225/100 |
| Open Issues | 3 |
| Last Updated | 2026-06-10 |
| Created | 2026-03-31 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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cc-mini is Ultra-light Harness scaffolding for AI agents, a mini version of claude code. It is categorized as a Agent Tool with 962 GitHub stars.
cc-mini is primarily written in Python.
You can find installation instructions and usage details in the cc-mini GitHub repository at github.com/e10nMa2k/cc-mini. The project has 962 stars and 357 forks, indicating an active community.
The top alternatives to cc-mini on Agent Skills Hub include excalidraw-diagram-skill, raptor, playwright-skill. 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: