# Adam v22.0 Remediation Backlog - Best Practices for [Open Source] Repo Dev + 

This document outlines the prioritized tasks for the development team to remediate the critical flaws in v21.0 and launch a robust, trustworthy "Adam v22.0."

## Priority 1: Foundational Trust & Safety (The "Non-Negotiables")

### Task: Implement Regulatory Compliance Agent
*   **User Story:** "As an institutional user, I must be confident that all analyses performed by the SNC Analyst Agent adhere to federal financial regulations (e.g., Fed, FDIC, OCC oversight)."

### Task: Implement Red Team Agent
*   **User Story:** "As an architect, I need an autonomous agent that continuously performs adversarial attacks (prompt injection, jailbreaks, data poisoning scenarios) on all other agents to test the 'Ethical Guardrails'."

### Task: Implement W3C PROV-O Provenance Layer (The "PDS")
*   **User Story:** "As an auditor, I must be able to trace any piece of data, analysis, or agent decision back to its origin. All agent interactions (Activities) and data points (Entities) must be logged as auditable PROV-O triples in the Neo4j Knowledge Graph."

### Task: Implement XAISkill
*   **User Story:** "As an analyst, I need to understand why the Fundamental Analysis Agent made a 'buy' recommendation. The system must provide a SHAP/LIME-style breakdown of the key features that influenced its decision."

## Priority 2: Architectural & "Cognitive" Refactoring

### Task: Refactor Meta-Cognitive Agent
*   **User Story:** "As the Meta-Cognitive Agent, I must now ingest the PROV-O-compliant reasoning graph from other agents, not just their text output. I will traverse this graph to detect logical fallacies, data gaps, or reasoning inconsistencies before the final answer is shown to the user."

### Task: Define & Implement Asynchronous Message Queue
*   **User Story:** "As a systems administrator, I need the agent communication layer to be scalable and resilient. All inter-agent communication must be refactored from direct calls to a message-broker system (e.g., RabbitMQ, Kafka, or Celery) to handle institutional-level workloads."

## Priority 3: Fulfilling Aspirational Claims

### Task: Implement CounterfactualReasoningSkill
*   **User Story:** "As a portfolio manager, I need to ask 'what-if' questions (e.g., 'What would be the impact on my portfolio if oil prices rose by 20%?'). This skill must leverage the Knowledge Graph's causal relationships."

### Task: Implement HybridForecastingSkill
*   **User Story:** "As a quant, I want the Technical Analysis Agent to use a robust, hybrid forecasting model (e.g., ARIMA + LSTM) for time-series predictions."