# Adam v23.5 Implementation Notes

## Overview

This document details the implementation of the "Sovereign Financial Intelligence Architecture" directives for Adam v23.5.

## Implemented Components

### 1. Infrastructure Modernization
*   **Module**: `src/mcp_server.py`
*   **Description**: Implemented a Model Context Protocol (MCP) server using `fastmcp`.
*   **Capabilities**:
    *   Exposes `calculate_wacc` and `calculate_dcf` as MCP tools.
    *   Exposes `market_data://{ticker}` as an MCP resource (simulated connection to Universal Ingestor).
    *   Migrated dependency management to `pyproject.toml` (simulating `uv` workflow).

### 2. Cognitive Core (HNASP)
*   **Modules**: `core/memory/hnasp_schema.py`, `core/memory/hnasp_engine.py`
*   **Description**: Implemented the Hybrid Neurosymbolic Agent State Protocol (HNASP).
*   **Details**:
    *   Defined Pydantic schemas for `MetaNamespace`, `LogicLayer`, `PersonaState` (EPA vectors), and `ContextStream`.
    *   Integrated `json-logic` for deterministic rule validation within the `HNASPEngine` middleware.

### 3. Financial Analyst (Quantum Risk)
*   **Module**: `core/risk_engine/quantum_model.py`
*   **Description**: Implemented a placeholder Quantum Amplitude Estimation (QAE) module.
*   **Details**:
    *   Designed the class structure to interface with `qiskit` (imports wrapped in try-except for environment compatibility).
    *   Implements `translate_risk_params` and `run_qae_simulation` methods.
    *   Provides classical fallback simulation if quantum backend is unavailable.

### 4. Red Team Construct (Adversarial AI)
*   **Modules**: `core/agents/skills/counterfactual_reasoning_skill.py`, `core/agents/red_team_agent.py`
*   **Description**: Enhanced the Red Team Agent with specific skills for stress testing.
*   **Details**:
    *   Created `CounterfactualReasoningSkill` to invert credit memo assumptions (e.g., "Bear Case" generation).
    *   Updated `RedTeamAgent` to utilize this skill within its internal LangGraph loop (`_generate_attack_node`).

### 5. Governance Architect (EACI)
*   **Modules**: `core/security/eaci_middleware.py`, `tests/golden_dataset.jsonl`, `.github/workflows/prompt_eval.yml`
*   **Description**: Implemented the Enterprise Adaptive Core Interface (EACI) framework.
*   **Details**:
    *   `EACIMiddleware` provides input sanitization (preventing prompt injection) and RBAC context injection.
    *   Established a "Golden Dataset" of expected financial queries for PromptOps regression testing.
    *   Created a GitHub Actions workflow scaffold for automated prompt evaluation.

## Next Steps

1.  **Full Qiskit Integration**: Once the environment supports heavy quantum libraries, remove the mocks in `quantum_model.py`.
2.  **Lakehouse Connection**: Connect `HNASPEngine` to a real object store (S3/MinIO) instead of local JSONL files.
3.  **Identity Provider**: Connect `EACIMiddleware` to a real OIDC provider for user role resolution.