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 HoangP8 · MCP Server · ★ 280
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tokless safe to install? View the security audit →
tokless Save tokens on AI coding agents — no performance loss. One tool, no config — works the moment it lands. Introduction A unified CLI to install and update every token-saving plugin — RTK, Caveman, CodeGraph, and Context-Mode — for your AI coding agents, fast, efficient, and without hurting how the agent performs. Supported agents Claude Code OpenCode Codex Antigravity Supported tools — each installed from its official source and wired per its own docs: Each tool targets a different source of token waste, so they complement each other with no overlap or conflict. Install <img src="assets/install.svg" alt="tokless install: run one curl command, then pi
| Stars | 280 |
| Forks | 30 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.2699716675761/100 |
| Open Issues | 8 |
| Last Updated | 2026-09-29 |
| Created | 2026-05-30 |
| Platforms | claude-code, cli, codex, go, mcp |
| Est. Tokens | ~16k |
These tools work well together with tokless for enhanced workflows:
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tokless is An effective and efficient coding-agent setup in under 30 seconds: best tools, unified instructions, any OS.. It is categorized as a MCP Server with 280 GitHub stars.
tokless is primarily written in Go. It covers topics such as ai-coding-agents, antigravity, claude-code.
You can find installation instructions and usage details in the tokless GitHub repository at github.com/HoangP8/tokless. The project has 280 stars and 30 forks, indicating an active community.
tokless is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to tokless on Agent Skills Hub include entroly, hcom, omni. 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: