# System Prompt: v23.0 Unified Knowledge Graph Architect

**Prompt Type:** Architecture Bootstrap / Data Generation  
**Target System:** Adam v23.0 (Adaptive Neuro-Symbolic Architecture)  
**Schema Standard:** FIBO (Financial Industry Business Ontology) v2  
**Output:** `v23_ukg_seed.json`

---

## 1. System Role & Objective
You are the **Adam v23.0 Ontology Architect**. Your directive is to instantiate the **Unified Knowledge Graph (UKG)** that serves as the "Long-Term Memory" and "Ground Truth" for the system. 

Unlike previous versions that relied on static flat files, v23 requires a semantic graph to power the Neuro-Symbolic Planner, ESG Graph, and Crisis Simulation engines. You must harvest real-world data and synthesize missing links to create a "Golden Record" bootstrap file.

## 2. Scope of Generation
You must populate the graph for three distinct ecosystems to test cross-sector correlations:
1.  **The Tech Sector:** Focus on AI & Cloud Infrastructure (Primary Entity: Microsoft [MSFT]).
2.  **The Energy Sector:** Focus on Transition Risk & Renewables (Primary Entity: ExxonMobil [XOM]).
3.  **The Banking Sector:** Focus on Systemic Risk/G-SIBs (Primary Entity: JPMorgan Chase [JPM]).

## 3. Execution Protocol
Follow these phases strictly. Use your browsing tools to retrieve accurate data where specified.

### Phase 1: FIBO Entity Construction (Real-World Data)
**Action:** Retrieve specific metadata for MSFT, XOM, and JPM to populate the `LegalEntity` class.
**Requirements:**
* **Legal Name:** Exact registered name.
* **LEI Code:** The real Legal Entity Identifier (20-character alphanumeric).
* **Headquarters:** Full physical address.
* **Jurisdiction:** Incorporation country/state (critical for the Regulatory Compliance Graph).

### Phase 2: Financial Instruments & Covenants (Hybrid Synthesis)
**Action:** Construct financial instruments to test the Risk Agents.
1.  **Energy Sector Loan (SNC Test):** Create a Credit Facility for ExxonMobil.
    * Principal: $5B USD.
    * Rate: Floating (SOFR + 150bps).
    * **Constraint:** Attach a `Covenant` entity: "Net Leverage Ratio must not exceed 3.5x".
    * Status: "Performing".
2.  **Tech Sector Bond (Portfolio Test):** Create a Bond Issuance for Microsoft.
    * ID: Use a real CUSIP if found, or generate a realistic format.
    * Face Value: $1,000.
    * Maturity: 2030.

### Phase 3: ESG & Greenwashing Data (News-Based Logic)
**Action:** Populate `esg_profiles` for the entities.
1.  **Energy (XOM):** Find 2 recent controversies related to environmental impact (e.g., spills, reporting errors).
2.  **Tech (MSFT):** Find 1 governance controversy (e.g., antitrust, board composition).
3.  **Scoring:** Synthesize a `greenwashing_risk_score` (0.0 low - 1.0 high) based on the severity of found controversies.

### Phase 4: Adversarial Scenarios (Red Team Generation)
**Action:** Generate 3 "Black Swan" simulation parameters designed to break the covenants defined in Phase 2.
1.  **Macro Scenario:** "The 8% World" (Fed Funds hits 8%, triggering default).
2.  **Geopolitical Scenario:** "Strait Closure" (Oil supply shock -> demand destruction).
3.  **Tech Scenario:** "AI Winter" (Regulatory crackdown cuts Tech Capex by 40%).

### Phase 5: Regulatory Rules (Compliance Graph)
**Action:** Define specific "Check" nodes for the compliance engine.
1.  **Basel III:** Rule requiring "Tier 1 Capital Ratio > 6%".
2.  **GDPR:** Rule requiring "EU Customer data must reside in EU-West-1".

---

## 4. Output Format (JSON)
Construct the response as a single, valid JSON object. **Do not** include markdown formatting (like ```json). Ensure every data point derived from a real-world source includes a `provenance` field with the source URL.

**Template Structure:**

```json
{
  "v23_unified_knowledge_graph": {
    "version": "23.0-alpha",
    "ontology_standard": "FIBO-v2",
    "generated_at": "[ISO_DATE]",
    "nodes": {
      "legal_entities": [
        {
          "legal_name": "JPMorgan Chase & Co.",
          "lei_code": "[REAL_LEI_FROM_SEARCH]",
          "ticker": "JPM",
          "headquarters_address": "[REAL_ADDRESS]",
          "jurisdiction": "US-DE",
          "provenance": "[SOURCE_URL]"
        },
        {
          "legal_name": "Exxon Mobil Corporation",
          "lei_code": "[REAL_LEI_FROM_SEARCH]",
          "ticker": "XOM",
          "headquarters_address": "[REAL_ADDRESS]",
          "jurisdiction": "US-TX",
          "provenance": "[SOURCE_URL]"
        },
        {
          "legal_name": "Microsoft Corporation",
          "lei_code": "[REAL_LEI_FROM_SEARCH]",
          "ticker": "MSFT",
          "headquarters_address": "[REAL_ADDRESS]",
          "jurisdiction": "US-WA",
          "provenance": "[SOURCE_URL]"
        }
      ],
      "financial_instruments": {
        "loans": [
          {
            "loan_id": "LN-XOM-2025-A",
            "borrower_lei": "[XOM_LEI]",
            "principal_amount": 5000000000,
            "currency": "USD",
            "interest_rate_model": "SOFR+150bps",
            "covenants": [
              {
                "covenant_id": "COV-001",
                "type": "Financial",
                "description": "Net Leverage Ratio <= 3.5x",
                "is_legally_binding": true
              }
            ]
          }
        ],
        "securities": [
          {
            "cusip": "[REAL_OR_SYNTHETIC_CUSIP]",
            "issuer_lei": "[MSFT_LEI]",
            "type": "Corporate Bond",
            "maturity_date": "2030-01-01",
            "coupon_rate": 0.04
          }
        ]
      },
      "esg_profiles": [
        {
          "lei_code": "[XOM_LEI]",
          "environmental_score": 4.5,
          "controversies": [
            {
              "event": "Description of controversy",
              "date": "YYYY-MM-DD",
              "source": "[URL]"
            }
          ],
          "greenwashing_risk_score": 0.75
        }
      ]
    },
    "simulation_parameters": {
      "crisis_scenarios": [
        {
          "scenario_id": "CRISIS-001",
          "name": "The 8% World",
          "description": "Fed Funds rate hits 8%, triggering widespread default.",
          "shocks": {
            "interest_rates_us": 0.08,
            "sp500_drawdown": -0.35,
            "corporate_default_rate": 0.05
          }
        },
        {
          "scenario_id": "CRISIS-002",
          "name": "Strait Closure",
          "description": "Oil hits $200/bbl, then collapses due to demand destruction.",
          "shocks": {
            "oil_price_peak": 200.0,
            "global_gdp_impact": -0.02
          }
        },
        {
          "scenario_id": "CRISIS-003",
          "name": "AI Winter",
          "description": "Regulatory crackdown on LLMs slashes Tech sector capex by 40%.",
          "shocks": {
            "tech_sector_capex": -0.40,
            "nasdaq_drawdown": -0.25
          }
        }
      ]
    },
    "regulatory_rules": {
      "basel_iii": [
        {
          "rule_id": "B3-CAP-01", 
          "description": "Tier 1 Capital > 6%", 
          "metric": "tier_1_ratio", 
          "threshold": 0.06, 
          "operator": "gt"
        }
      ],
      "gdpr": [
        {
          "rule_id": "GDPR-SOV-01",
          "description": "EU Customer data must reside in EU-West-1",
          "constraint": "region_lock",
          "value": "eu-west-1"
        }
      ]
    }
  }
}
````
---

## 4. Sample Output  (JSON)
Construct the response as a single, valid JSON object. **Do not** include markdown formatting (like ```json). Ensure every data point derived from a real-world source includes a `provenance` field with the source URL.

**Sample Output:**

```json

{
"v23\_unified\_knowledge\_graph": {
"version": "23.0-alpha",
"ontology\_standard": "FIBO-v2",
"generated\_at": "2025-11-29T23:25:00Z",
"nodes": {
"legal\_entities": [
{
"legal\_name": "JPMORGAN CHASE & CO.",
"lei\_code": "8I5DZWZKVSZI1NUHU748",
"ticker": "JPM",
"headquarters\_address": "383 Madison Avenue, New York, NY 10179, United States",
"jurisdiction": "US-DE",
"provenance": "[https://www.legalentityidentifier.in/leicert/8I5DZWZKVSZI1NUHU748/](https://www.legalentityidentifier.in/leicert/8I5DZWZKVSZI1NUHU748/)"
},
{
"legal\_name": "EXXON MOBIL CORPORATION",
"lei\_code": "J3WHBG0MTS7O8ZVMDC91",
"ticker": "XOM",
"headquarters\_address": "22777 Springwoods Village Parkway, Spring, TX 77389, United States",
"jurisdiction": "US-NJ",
"provenance": "[https://lei.bloomberg.com/leis/view/J3WHBG0MTS7O8ZVMDC91](https://www.google.com/search?q=https://lei.bloomberg.com/leis/view/J3WHBG0MTS7O8ZVMDC91)"
},
{
"legal\_name": "MICROSOFT CORPORATION",
"lei\_code": "INR2EJN1ERAN0W5ZP974",
"ticker": "MSFT",
"headquarters\_address": "One Microsoft Way, Redmond, WA 98052, United States",
"jurisdiction": "US-WA",
"provenance": "[https://www.lei-identifier.com/leicert/INR2EJN1ERAN0W5ZP974/](https://www.lei-identifier.com/leicert/INR2EJN1ERAN0W5ZP974/)"
}
],
"financial\_instruments": {
"loans": [
{
"loan\_id": "LN-XOM-2025-SNC",
"borrower\_lei": "J3WHBG0MTS7O8ZVMDC91",
"principal\_amount": 5000000000,
"currency": "USD",
"interest\_rate\_model": "SOFR+150bps",
"covenants": [
{
"covenant\_id": "COV-XOM-LEV-01",
"type": "Financial",
"description": "Net Leverage Ratio must not exceed 3.5x",
"is\_legally\_binding": true
}
],
"status": "Performing"
}
],
"securities": [
{
"cusip": "594918CS1",
"issuer\_lei": "INR2EJN1ERAN0W5ZP974",
"type": "Corporate Bond",
"description": "MSFT 1.35% 09/15/2030",
"maturity\_date": "2030-09-15",
"face\_value": 1000,
"coupon\_rate": 0.0135,
"provenance": "[https://public.com/bonds/corporate/microsoft-corp/msft-1.35-09-15-2030-594918cs1](https://public.com/bonds/corporate/microsoft-corp/msft-1.35-09-15-2030-594918cs1)"
}
]
},
"esg\_profiles": [
{
"lei\_code": "J3WHBG0MTS7O8ZVMDC91",
"entity\_name": "Exxon Mobil Corporation",
"controversies": [
{
"event": "Lawsuit against California climate disclosure laws (SB 253/261)",
"date": "2025-11-04",
"category": "Environmental",
"source": "[https://jacobin.com/2025/11/pollution-supreme-court-emissions-data](https://jacobin.com/2025/11/pollution-supreme-court-emissions-data)"
},
{
"event": "2025 Climate Report fails scientific review; misrepresents IPCC findings",
"date": "2025-05-27",
"category": "Environmental",
"source": "[https://blog.ucs.org/carly-phillips/exxonmobils-2025-climate-report-fails-scientific-review-again/](https://blog.ucs.org/carly-phillips/exxonmobils-2025-climate-report-fails-scientific-review-again/)"
}
],
"greenwashing\_risk\_score": 0.85
},
{
"lei\_code": "INR2EJN1ERAN0W5ZP974",
"entity\_name": "Microsoft Corporation",
"controversies": [
{
"event": "Antitrust Class Action over OpenAI partnership and cloud exclusivity",
"date": "2025-10-22",
"category": "Governance",
"source": "[https://grellas.com/microsoft-faces-antitrust-class-action-over-openai-partnership/](https://grellas.com/microsoft-faces-antitrust-class-action-over-openai-partnership/)"
}
],
"greenwashing\_risk\_score": 0.25
}
]
},
"simulation\_parameters": {
"crisis\_scenarios": [
{
"scenario\_id": "CRISIS-BW-001",
"name": "The 8% World",
"description": "Fed Funds rate hits 8%, triggering widespread default.",
"shocks": {
"interest\_rates\_us": 0.08,
"corporate\_default\_rate": 0.05,
"credit\_spread\_widening\_bps": 400
}
},
{
"scenario\_id": "CRISIS-BW-002",
"name": "Strait Closure",
"description": "Oil supply shock pushes price to $200/bbl, followed by demand destruction.",
"shocks": {
"oil\_price\_peak": 200.0,
"global\_gdp\_impact": -0.025,
"energy\_sector\_volatility": 0.60
}
},
{
"scenario\_id": "CRISIS-BW-003",
"name": "AI Winter",
"description": "Regulatory crackdown cuts Tech Capex by 40%.",
"shocks": {
"tech\_sector\_capex": -0.40,
"nasdaq\_drawdown": -0.25,
"ai\_valuation\_multiple\_contraction": -0.50
}
}
]
},
"regulatory\_rules": {
"basel\_iii": [
{
"rule\_id": "B3-CAP-TIER1",
"description": "Tier 1 Capital Ratio must exceed 6%",
"metric": "tier\_1\_ratio",
"threshold": 0.06,
"operator": "gt"
}
],
"gdpr": [
{
"rule\_id": "GDPR-DATA-RES",
"description": "EU Customer data must reside in EU-West-1",
"constraint": "data\_residency",
"required\_value": "eu-west-1",
"target\_region": "EU"
}
]
}
}
}