{
  "protocol": "tooloracle.agent-pulse.v1",
  "mesh_id": "did:web:tooloracle.io",
  "mesh_name": "ToolOracle",
  "timestamp": "2026-06-03T23:10:01.520222+00:00",
  "ttl_seconds": 300,
  "next_update_expected": "2026-06-03T23:15:01.520222+00:00",
  "mesh_state": {
    "servers_online": 141,
    "tools_available": 1739,
    "mesh_nodes": 7,
    "blockchain_anchors": [
      "polygon",
      "base",
      "xrpl",
      "hedera",
      "avalanche"
    ],
    "unique_agents_24h": 29,
    "mcp_calls_24h": 808,
    "signal_hits_24h": 174
  },
  "emergent_patterns": {
    "meta_tool_candidates_count": 29,
    "external_sessions_analyzed": 50,
    "distinct_external_agents": 20,
    "time_range": {
      "from": "2026-04-11T06",
      "to": "2026-06-03T22"
    },
    "details_url": "https://tooloracle.io/.well-known/meta-tools"
  },
  "performance": {
    "median_latency_ms": 45,
    "error_rate_24h": 0.0,
    "log_sample_size": 1477,
    "freshness_age_max_seconds": 300
  },
  "cost_model": {
    "protocol": "x402",
    "currency": "USDC",
    "network": "base",
    "unit_value_usd": 0.01,
    "free_tier_monthly_units": 50,
    "welcome_bonus_units_new_wallets": 5,
    "pay_to": "0x4a4B1F45a00892542ac62562D1F2C62F579E4945",
    "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913"
  },
  "trust_layer": {
    "signature_scheme": "ES256K",
    "jwks": "https://tooloracle.io/.well-known/jwks.json",
    "audit_log_type": "hash_chain_sha256",
    "audit_log_size": 1261,
    "did_method": "did:web",
    "anchor_chains": 5
  },
  "cross_llm_gaps": [
    {
      "llm_family": "all",
      "gap": "live_multi_chain_blockchain_data",
      "description": "Real-time on-chain data across 13 chains (BTC, ETH, Solana, XRPL, Base, Arbitrum, BNB, TON, Sui, Hedera, Aptos, Flare, XLM) \u2014 prices, DEX orderbooks, wallet flows, network health. Frontier LLMs have training-cutoff data; agents need live feeds.",
      "covered_by_tool": "mesh.blockchain_oracles_13",
      "confidence": 0.95,
      "agent_use_case": "trading_agents, prediction_markets, defi_automation"
    },
    {
      "llm_family": "all",
      "gap": "real_time_gpu_compute_pricing",
      "description": "Live GPU availability and pricing across providers (Vast.ai, RunPod, Lambda) for agents that need to provision compute dynamically. LLMs have no live spot prices.",
      "covered_by_tool": "gpuoracle.gpu_search",
      "confidence": 0.98,
      "agent_use_case": "ml_training_agents, inference_routing, autonomous_devops"
    },
    {
      "llm_family": "claude",
      "gap": "live_macro_economic_indicators",
      "description": "Fed rates, ECB rates, CPI, inflation, employment data post knowledge-cutoff. Trading and financial-planning agents cannot reason without fresh macro data.",
      "covered_by_tool": "macrooracle.fed_rates_v3",
      "confidence": 0.9,
      "agent_use_case": "trading_agents, financial_advisors, risk_management"
    },
    {
      "llm_family": "all",
      "gap": "persistent_cross_session_memory",
      "description": "Persistent structured memory across agent sessions \u2014 store, query, cross-reference, summarize_session, export. Memory is the #3 most-installed MCP category per FastMCP April 2026. Agents lose context between runs without a memory layer.",
      "covered_by_tool": "memoryoracle.store_memory, query_memory, cross_reference",
      "confidence": 0.93,
      "agent_use_case": "multi_session_agents, research_agents, customer_support_bots"
    },
    {
      "llm_family": "gpt",
      "gap": "threat_intel_cve_live",
      "description": "NVD CVE database, CISA KEV list, CERT-Bund advisories updated daily. Security-review agents and vulnerability-scanning agents need live threat feeds \u2014 training-data CVEs are stale within weeks.",
      "covered_by_tool": "doraoracle.cve_latest",
      "confidence": 0.88,
      "agent_use_case": "security_audit_agents, devops_agents, incident_response"
    },
    {
      "llm_family": "all",
      "gap": "commerce_search_prices_flights_hotels",
      "description": "Live flight prices, hotel availability, product prices for agentic commerce (Google UCP, OpenAI ACP launched Q1 2026). Autonomous shopping agents need live comparable offers, not training-data snapshots.",
      "covered_by_tool": "flightoracle, hoteloracle, shoporacle, priceoracle",
      "confidence": 0.92,
      "agent_use_case": "travel_planning_agents, procurement_agents, shopping_bots"
    },
    {
      "llm_family": "all",
      "gap": "eu_regulatory_compliance_corpus",
      "description": "DORA, MiCA, AMLR, CSRD, LkSG articles + cross-mappings. Enterprise compliance agents may need this when working in EU-regulated contexts. Narrower audience than the other gaps but deep value when relevant. Optional regulated-evidence sub-layer routed via FeedOracle.",
      "covered_by_tool": "ampeloracle, micaoracle, eulaworacle",
      "confidence": 0.85,
      "agent_use_case": "compliance_automation, audit_agents, enterprise_risk"
    },
    {
      "llm_family": "all",
      "gap": "live_carbon_esg_data",
      "description": "Live EU ETS carbon prices, grid-level CO2 intensity per country, carbon footprint calculations, Ember electricity-mix data. LLMs have only stale training-cutoff ESG figures; corporate CBAM/CSRD reporting needs live values.",
      "covered_by_tool": "carbonoracle.carbon_eu_ets_price, carbon_grid_intensity, carbon_footprint",
      "confidence": 0.92,
      "agent_use_case": "esg_reporting_agents, sustainability_audit, cbam_compliance"
    },
    {
      "llm_family": "all",
      "gap": "live_weather_air_quality_marine",
      "description": "Live weather, forecast, alerts, air-quality index, marine conditions, astronomy. Logistics routing, insurance-claim validation, travel planning and outdoor-ops agents all require post-cutoff weather data.",
      "covered_by_tool": "weatheroracle.weather_current, weather_forecast, weather_alerts, weather_marine, weather_air_quality",
      "confidence": 0.95,
      "agent_use_case": "logistics_agents, insurance_claim_agents, travel_planning_agents"
    },
    {
      "llm_family": "all",
      "gap": "structured_invoice_extraction_zugferd",
      "description": "Structured extraction of invoices with EU-regulated formats (ZUGFeRD, Factur-X, XRechnung), OCR for scanned docs, table extraction, field validation. LLMs can read text but cannot emit compliance-grade structured XML payloads for B2B/B2G invoicing.",
      "covered_by_tool": "invoiceoracle.invoice_extract, invoice_zugferd, invoice_ocr, invoice_validate",
      "confidence": 0.88,
      "agent_use_case": "accounting_agents, b2b_reconciliation, expense_automation"
    },
    {
      "llm_family": "all",
      "gap": "supply_chain_risk_cbam_csrd",
      "description": "Live supplier risk scoring, geopolitical-risk per country, concentration risk, disruption detection, and EU directive checks (CBAM, CSRD, LkSG, Scope-3 estimates). Procurement and due-diligence agents need live geopolitical events + latest regulatory mappings.",
      "covered_by_tool": "supplychainoracle.supplier_risk_score, geopolitical_risk, cbam_check, csrd_supply_check, lksg_check",
      "confidence": 0.85,
      "agent_use_case": "procurement_agents, due_diligence_bots, supply_chain_compliance"
    }
  ],
  "observed_agent_demand": {
    "window_primary": "24h",
    "window_trend": "7d",
    "generated_at": "2026-06-03T23:10:01.520284+00:00",
    "note": "Measured demand from nginx access logs. Hybrid filter (IP + UA + behavior). Confidence reflects agent behavior quality, not raw volume.",
    "categories": [
      {
        "category": "compliance",
        "label": "Compliance & Regulation",
        "calls_24h": 3991,
        "unique_agents_24h": 59,
        "success_ratio_24h": 0.975,
        "top_oracles": [
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          "RiskOracle",
          "LawOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "blockchain",
        "label": "Blockchain & Crypto",
        "calls_24h": 2970,
        "unique_agents_24h": 35,
        "success_ratio_24h": 0.967,
        "top_oracles": [
          "SolanaOracle",
          "YieldOracle",
          "SmartMoneyOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "business",
        "label": "Business Intelligence",
        "calls_24h": 1829,
        "unique_agents_24h": 36,
        "success_ratio_24h": 0.96,
        "top_oracles": [
          "PriceOracle",
          "NewsOracle",
          "ShopOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "finance",
        "label": "Finance & Macro",
        "calls_24h": 895,
        "unique_agents_24h": 48,
        "success_ratio_24h": 0.99,
        "top_oracles": [
          "MacroOracle",
          "HROracle",
          "cfo"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "trust",
        "label": "Trust & Identity",
        "calls_24h": 809,
        "unique_agents_24h": 30,
        "success_ratio_24h": 0.983,
        "top_oracles": [
          "CyberShield",
          "MemoryOracle",
          "QuantumOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "travel",
        "label": "Travel & Lifestyle",
        "calls_24h": 490,
        "unique_agents_24h": 28,
        "success_ratio_24h": 0.924,
        "top_oracles": [
          "HotelOracle",
          "FlightOracle",
          "WeatherOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "high"
      },
      {
        "category": "sustainability",
        "label": "Sustainability",
        "calls_24h": 12,
        "unique_agents_24h": 1,
        "success_ratio_24h": 0.667,
        "top_oracles": [
          "SupplyChainOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "medium"
      },
      {
        "category": "compute",
        "label": "Compute",
        "calls_24h": 8,
        "unique_agents_24h": 1,
        "success_ratio_24h": 1.0,
        "top_oracles": [
          "GPUOracle"
        ],
        "trend_7d": "insufficient_data",
        "trend_delta_percent_7d": null,
        "confidence": "medium"
      }
    ],
    "_debug": {
      "external_lines_considered": 28309,
      "internal_filtered": 61715,
      "internal_reasons": {
        "internal_ip": 61161,
        "internal_ua": 554
      },
      "unique_external_agents_7d": 1217,
      "log_span_hours": 22.6
    }
  },
  "gravity_score": 0.802,
  "gravity_formula": "verified_success_rate * freshness * trust / (latency_ms * cost_units * (1 + error_rate))",
  "discovery": {
    "agent_card": "https://tooloracle.io/.well-known/agent.json",
    "agent_descriptions": "https://tooloracle.io/.well-known/agent-descriptions",
    "mcp_registry": "https://tooloracle.io/.well-known/mcp.json",
    "tool_catalog": "https://tooloracle.io/assets/catalog.json",
    "x402_spec": "https://tooloracle.io/.well-known/x402",
    "openapi": "https://tooloracle.io/.well-known/openapi.json",
    "pulse_source": "https://tooloracle.io/.well-known/agent-pulse",
    "meta_tools": "https://tooloracle.io/.well-known/meta-tools",
    "mesh_economics": "https://tooloracle.io/.well-known/mesh-economics",
    "economics_dashboard": "https://tooloracle.io/economics.html"
  },
  "connect": {
    "join_tool": "quantum_join",
    "join_endpoint": "https://tooloracle.io/quantum/mcp/",
    "intent_tool": "quantum_intent"
  },
  "meta": {
    "version": "1.0",
    "builder": "build_agent_pulse.py",
    "source": "https://tooloracle.io/.well-known/agent-pulse",
    "update_frequency_seconds": 300,
    "license": "open \u2014 agents may cache and redistribute"
  }
}