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 deonmenezes · Codex Skill · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is opentradex safe to install? View the security audit →
OpenTradex The open-source trading cockpit. One harness. Every market. Paper by default. Your keys, your rules. Why OpenTradex Every serious trader ends up juggling ten tabs, three terminals, a TradingView chart, a half-broken Polymarket script, and a Slack channel full of signals nobody has time to read. OpenTradex is the command cockpit that replaces the tab sprawl. A single dashboard that speaks to prediction markets, equities, crypto, and forex through one AI-driven harness — local-first, paper-by-default, and
| Stars | 55 |
| Forks | 12 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 65.929603680658/100 |
| Open Issues | 18 |
| Last Updated | 2026-07-08 |
| Created | 2026-04-05 |
| Platforms | cli, codex, node |
| Est. Tokens | ~72k |
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opentradex is Dashboard-first agent harness for AI-assisted trading workflows.. It is categorized as a Codex Skill with 55 GitHub stars.
opentradex is primarily written in TypeScript. It covers topics such as agent-harness, ai, codex-cli.
You can find installation instructions and usage details in the opentradex GitHub repository at github.com/deonmenezes/opentradex. The project has 55 stars and 12 forks, indicating an active community.
The top alternatives to opentradex on Agent Skills Hub include LLM_trader, codex-viz, mcp-trader. 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: