juno-code — security grade SAFE, quality 70/100

Security audit verdict: SAFE · quality 70/100

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 askbudi · Codex Skill · ★ 56

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About juno-code

juno-code AI-powered code automation with structured task management Installation After installation, initialize your project: Shell Completion (Tab Autocomplete) After installation/reload, suggests available subcommands. The Ralph Method: Where It All Started "I'm in danger!" - Ralph Wi

ai-agentautonomous-agentsbacklog-ralphclaude-codecodex-clicursor-cliopencodepi-agentralph-loopralph-wiggum

Quick Facts

Stars56
Forks5
LanguageTypeScript
CategoryCodex Skill
Quality Score69.636977669813/100
Last Updated2026-08-17
Created2026-01-06
Platformsclaude-code, cli, codex, node
Est. Tokens~23k

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Frequently Asked Questions

What is juno-code?

juno-code is Ralph Wiggum meet Kanban! Ralph style execution for [Claude Code, Codex, Pi, Cursor]. One task per iteration, automatic progress tracking, and git commits. Set it and let it run.. It is categorized as a Codex Skill with 56 GitHub stars.

What programming language is juno-code written in?

juno-code is primarily written in TypeScript. It covers topics such as ai-agent, autonomous-agents, backlog-ralph.

How do I install or use juno-code?

You can find installation instructions and usage details in the juno-code GitHub repository at github.com/askbudi/juno-code. The project has 56 stars and 5 forks, indicating an active community.

What are the best alternatives to juno-code?

The top alternatives to juno-code on Agent Skills Hub include yylo, unigent, ralph-starter. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools