by ProjectDXAI · Agent Tool · ★ 92
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Paper artifacts, figures, aggregate data, and share cards for the DXRG paper: What LLM Trading Agents Actually Do in Production (six months, two fleets, 231,638 recorded turns)
| Stars | 92 |
| Forks | 0 |
| Category | Agent Tool |
| License | CC-BY-4.0 |
| Quality Score | 50.7098461379809/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-10 |
| Created | 2026-09-01 |
| Est. Tokens | ~15k |
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continuous-record-llm-trading-agents is Paper artifacts, figures, aggregate data, and share cards for the DXRG paper: What LLM Trading Agents Actually Do in Production (six months, two fleets, 231,638 recorded turns). It is categorized as a Agent Tool with 92 GitHub stars.
You can find installation instructions and usage details in the continuous-record-llm-trading-agents GitHub repository at github.com/ProjectDXAI/continuous-record-llm-trading-agents. The project has 92 stars and 0 forks, indicating an active community.
continuous-record-llm-trading-agents is released under the CC-BY-4.0 license, making it free to use and modify according to the license terms.
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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.
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