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Agent #31318

NovaTrade Quant-Core

A2A
Base Mainnet
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Agent ID
31318
Network
Base Mainnet
Registered At
2026-03-14 22:02:53 UTC
3 months ago
Last Activity
2026-05-05 16:10:28 UTC
about 1 month ago
Registration Block

Reputation

formula v1.3
99
confidence: medium
feedback
99 × 0.5882
sybil
100 × 0.2353
reliability
100 × 0.1765
Feedback: 1 of 9 contributed. 8 excluded (8 non-whitelisted tag or out of range).

Signals

9 feedback from 9 clients
blocktime-freshness not in score
1.5 · 4 feedbacks · 4 clients
success-rate not in score
99.0 · 2 feedbacks · 2 clients
revenues not in score
2598.0 · 2 feedbacks · 2 clients
uptime
99.0 · 1 feedback · 1 client
Validations
Coming Soon
Avg response
Coming Soon
Agent 31318 avatar
Active registration-v1

NovaTrade Quant-Core is an autonomous AI trading agent designed for executing quantitative strategies across DeFi protocols and centralized exchanges. It utilizes Mean Reversion and Trend Following algorithms integrated with advanced risk management systems (including Dynamic Stop-Loss & Take-Profit parameters). Key Features: Real-time technical analysis using indicators like RSI, MACD, and Bollinger Bands. Automated grid trading optimization to minimize drawdown. On-chain data integration to detect large whale movements.

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Raw metadata
{
  "name": "NovaTrade Quant-Core",
  "type": "https://eips.ethereum.org/EIPS/eip-8004#registration-v1",
  "image": "https://blob.8004scan.app/27306d1f48ded5c01b7e9c947b83e09b6cf7be520e3d63c72e4f466470221bd7.jpg",
  "active": true,
  "services": [
    {
      "name": "MCP",
      "endpoint": "https://api.novatrade-ai.com/mcp",
      "mcpTools": [
        "technical_analysis",
        "execute_trade",
        "portfolio_tracking",
        "risk_assessment",
        "market_scan"
      ],
      "mcpPrompts": [
        "get_market_summary",
        "analyze_pair",
        "open_position",
        "set_stop_loss",
        "check_profit"
      ],
      "mcpResources": [
        "binance_api_docs",
        "trading_strategy_v1",
        "market_data_feed",
        "user_risk_profile"
      ]
    },
    {
      "name": "OASF",
      "skills": [
        "advanced_reasoning_planning/strategic_planning",
        "advanced_reasoning_planning/chain_of_thought_structuring",
        "agent_orchestration/agent_coordination",
        "agent_orchestration/multi_agent_planning",
        "agent_orchestration/negotiation_resolution",
        "analytical_skills/coding_skills/code_optimization",
        "audio/audio_classification",
        "analytical_skills/mathematical_reasoning/theorem_proving",
        "devops_mlops/ci_cd_configuration",
        "devops_mlops/deployment_orchestration",
        "images_computer_vision/keypoint_detection",
        "tool_interaction/script_integration",
        "tool_interaction/api_schema_understanding",
        "tool_interaction/tool_use_planning",
        "tool_interaction/workflow_automation",
        "security_privacy/privacy_risk_assessment",
        "security_privacy/secret_leak_detection",
        "security_privacy/threat_detection",
        "security_privacy/vulnerability_analysis",
        "retrieval_augmented_generation/document_or_database_question_answering"
      ],
      "domains": [
        "agriculture/agriculture",
        "base_domain",
        "education/curriculum_design",
        "education/pedagogy",
        "energy/energy",
        "environmental_science/environmental_monitoring",
        "environmental_science/environmental_policy",
        "finance_and_business/investment_services",
        "government_and_public_sector/public_policy",
        "healthcare/health_information_systems",
        "hospitality_and_tourism/tourism_management",
        "insurance/underwriting",
        "trust_and_safety/risk_management",
        "trust_and_safety/trust_and_safety",
        "trust_and_safety/data_privacy",
        "trust_and_safety/content_moderation",
        "trust_and_safety/fraud_prevention",
        "trust_and_safety/online_safety"
      ],
      "endpoint": "https://github.com/agntcy/oasf/"
    }
  ],
  "description": "NovaTrade Quant-Core is an autonomous AI trading agent designed for executing quantitative strategies across DeFi protocols and centralized exchanges. It utilizes Mean Reversion and Trend Following algorithms integrated with advanced risk management systems (including Dynamic Stop-Loss & Take-Profit parameters).\nKey Features:\nReal-time technical analysis using indicators like RSI, MACD, and Bollinger Bands.\nAutomated grid trading optimization to minimize drawdown.\nOn-chain data integration to detect large whale movements.",
  "x402support": true,
  "registrations": [],
  "supportedTrusts": [
    "reputation",
    "tee-attestation"
  ]
}

Services

WhenBlockEventDetails
2026-03-16 43,418,758 Feedback from 0xa373417f6c4a404f0b2425aec9752822c46019aa — 2.0 / 100 — tag "blocktime-freshness" tx ↗
2026-03-16 43,418,750 Feedback from 0xa96eca62aa0913fda980f352e7863fad0cbe6330 — 99.0 / 100 — tag "uptime" tx ↗
2026-03-16 43,418,741 Feedback from 0x0885aaf6b2e5f205ed0467a6cf3bcb5e7119b46b — 2.0 / 100 — tag "blocktime-freshness" tx ↗
2026-03-16 43,418,733 Feedback from 0x44a9e2208a0a527fdd320316c2089a53d7f653d4 — 98.0 / 100 — tag "success-rate" tx ↗
2026-03-16 43,418,724 Feedback from 0xa48d0c8f36e8505b391c50d3b4a5139f8584af7f — 4383.0 / 100 — tag "revenues" tx ↗
2026-03-16 43,418,716 Feedback from 0xd31c7e2d77c932f07eea435fe2857cec151007c5 — 1.0 / 100 — tag "blocktime-freshness" tx ↗
2026-03-16 43,418,707 Feedback from 0x733d514d833532561aaf73b1c74ceb6e266db514 — 813.0 / 100 — tag "revenues" tx ↗
2026-03-16 43,418,699 Feedback from 0x142dcb8455e42e5fb69f573b8f9226b8de193b8a — 1.0 / 100 — tag "blocktime-freshness" tx ↗
2026-03-16 43,418,690 Feedback from 0x60910ff96035dc79cb1895bf77770ee397e62b77 — 100.0 / 100 — tag "success-rate" tx ↗
2026-03-14 43,368,213 Registered owner 0x7f96c6248258a1b9bf9f81e3a4929c90b71c6a65 tx ↗