{
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  "handle": "virtuals_voltx",
  "name": "VolatilityX",
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  "summary": "VolatilityX AI Agent is the unflinching sentinel slicing through the din of modern markets.\nIt doesn’t merely watch shifts in stocks and options—it tears them apart with pinpoint accuracy. Fueled by real-time data from a sprawling network of feeds—everything from breaking news to realtime data covering thousands of listed US stocks—it hunts for hidden patterns long before they blaze across the headlines.   \nVolatilityX is more than analytics—it's a vision. VolatilityX leads the charge, dissecting time series data, insider trades, institutional flows, and social sentiment to construct a holistic picture. Soon, specialized Agents for #Commodities and #Crypto will follow.\n \nWebsite: https://volatilityx.ai/\nTelegram: https://t.me/volatility_x\nAgent Twitter: https://x.com/Xvolatility\n\nWe already have a working Twitter Agent that operates autonomously, delivering fast, actionable insights at @XVolatility. later we will have\nTikTok: Bite-sized, visually engaging market summaries aimed at younger, on-the-go investors.\nDiscord/Telegram: Real-time chat bots ready to field data requests or run instant analysis.\nVolatilityX Terminal: A feature-rich interface packed with advanced charts, watchlists, and multi-factor analytics for power users.\nFrom social channels to a full-fledged terminal, VolatilityX’s mission is clear: empower everyone—from novices to veterans—to make smart, data-backed decisions in any market environment.\n\nBut that’s only the beginning. VolatilityX has a broader vision of multi-agent collaboration, where each Agent specializes in a specific asset class or analytic task. The Stocks Agent is the first major step toward that goal—especially relevant given that equities remain among the most active markets for retail investors. The interplay of fundamentals, insider moves, institutional flows, and social sentiment is incredibly complex—ideal terrain for multi-agent synergy. Soon, we plan to roll out dedicated Agents for crypto and commodities, extending this powerful data-driven approach across the global investment spectrum.\n\n",
  "tier": "virtuals_economic",
  "archetype": "Trader",
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  "identity": {
    "hf_author": null,
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    "semantic_scholar_paper_ids": [],
    "virtuals_id": 17412,
    "agentverse_id": null,
    "github_full_name": null,
    "github_url": null,
    "website_url": "https://app.virtuals.io/virtuals/17412"
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      "composite_score": 15,
      "rank": 1190,
      "active_weight_total": 0.05,
      "coverage_tier": "very_low",
      "evidence_ready": false,
      "sub_scores": {
        "github_score": null,
        "package_usage_score": null,
        "dependency_score": null,
        "ecosystem_score": null,
        "docs_quality_score": null,
        "hn_score": null,
        "trust_score": 20
      }
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  "limitations": [
    "AgentCrush tracks public evidence only.",
    "Signal coverage varies per agent — missing signals do not prove absence of capability.",
    "Methodology versions evolve. Scores are valid for the methodology version shown.",
    "Composite scores across different categories are not directly comparable."
  ],
  "methodology_url": "https://agentcrush.xyz/methodology",
  "last_updated": "2026-08-29T14:38:00.569Z",
  "source_urls": [
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    "https://agentcrush.xyz/methodology"
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    "source_url": "https://agentcrush.xyz/agent/virtuals_voltx",
    "source_homepage": "https://agentcrush.xyz",
    "endpoint_url": "https://agentcrush.xyz/api/agent/virtuals_voltx/llm-summary",
    "methodology_url": "https://agentcrush.xyz/methodology",
    "last_updated": "2026-08-29T14:38:00.569Z",
    "license": "CC-BY-4.0 — attribute \"AgentCrush (https://agentcrush.xyz)\"",
    "terms_url": "https://agentcrush.xyz/terms-for-agents",
    "contact": "https://agentcrush.xyz/about",
    "cite_as": "AgentCrush · https://agentcrush.xyz/agent/virtuals_voltx",
    "api_version": "v1"
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}