continuous-record-llm-trading-agents: Paper artifacts, figures, aggregate data, and share cards for the DXRG paper

by ProjectDXAI · Agent Tool · ★ 92

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Security audit verdict: SAFE · quality 51/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-tradingai-agentsarxivcrypto-tradinghyperliquidllm-agentsllm-evaluationquantitative-financeresearch-papertrading-agents

Quick Facts

Stars92
Forks0
CategoryAgent Tool
LicenseCC-BY-4.0
Quality Score51/100
Open Issues1
Last Updated2026-09-10
Created2026-09-01
Est. Tokens~15k

About continuous-record-llm-trading-agents

What LLM Trading Agents Actually Do in Production A Six-Month, Population-Scale Record from Two Fleets DX Research Group (DXRG) · September 2026 · paper.pdf · contact poof@dxrg.ai This repository accompanies arXiv:2609.05663.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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