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 PabloNAX · Codex Skill · ★ 174
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ultracode-skill safe to install? View the security audit →
Ultracode Skill Ultracode Skill gives Codex a dynamic workflow layer for serious coding tasks. Use it when a task needs more than one pass: discovery, implementation, review, tests, and a final integration step. The skill tells the agent how to decide between a direct edit, a packetized workflow, or native agent delegation. Codex is the main target. Claude Code already has first-class workflow concepts; Codex has native multi-agent tools, but users still need a clean operating pattern around them. Ultracode fills that gap with one small folder. What it does Ultracode asks the agent to: Define the goal and success criteria. Decide whether the task needs direct, workflow, or delegated mode. Create workflow artifacts for non-trivial work. Use native agents when they are useful and allow
| Stars | 174 |
| Forks | 8 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 74.4104516484727/100 |
| Last Updated | 2026-06-15 |
| Created | 2026-05-31 |
| Platforms | claude-code, codex, gemini |
| Est. Tokens | ~17k |
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ultracode-skill is Codex-first Ultracode skill for dynamic coding workflows. It is categorized as a Codex Skill with 174 GitHub stars.
You can find installation instructions and usage details in the ultracode-skill GitHub repository at github.com/PabloNAX/ultracode-skill. The project has 174 stars and 8 forks, indicating an active community.
ultracode-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ultracode-skill on Agent Skills Hub include ai-workflow, Overture, kindly-web-search-mcp-server. 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: