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 OpenTradeOSS · Claude Skill · ★ 218
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OpenTrade safe to install? View the security audit →
The open-source trading harness for Claude Code / Codex agents. OpenTrade is a macOS app that enables agents to trade and react to the market autonomously. Agents execute trades in your Robinhood Agentic Trading account through the official MCP. Set guardrails, monitors, and schedules so agents can trade 24/7 - all on your machine. Features Monitor
| Stars | 218 |
| Forks | 19 |
| Language | TypeScript |
| Category | Claude Skill |
| Quality Score | 63.5671999495786/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-22 |
| Created | 2026-06-28 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~15k |
These tools work well together with OpenTrade for enhanced workflows:
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OpenTrade is The open-source trading harness for Claude Code / Codex agents.. It is categorized as a Claude Skill with 218 GitHub stars.
OpenTrade is primarily written in TypeScript. It covers topics such as agent, background-jobs, claude-code.
You can find installation instructions and usage details in the OpenTrade GitHub repository at github.com/OpenTradeOSS/OpenTrade. The project has 218 stars and 19 forks, indicating an active community.
The top alternatives to OpenTrade on Agent Skills Hub include hcom, Pane, genie. 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: