From a2be51bef132ee412c3e135b51a2af8677c4468e Mon Sep 17 00:00:00 2001
From: Sumeyaaaa <sumeyasirmulach@gmail.com>
Date: Wed, 18 Feb 2026 11:16:42 +0300
Subject: [PATCH] docs: Add Architecture.md for challenge documentation

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 Architecture.md | 169 ++++++++++++++++++++++++++++++++++++++++++++++++
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 create mode 100644 Architecture.md

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+
+## **1. Project Overview**
+
+**Goal:**
+Develop an **Intent-Code Traceability system** for the AI-Native IDE that ensures AI-generated code aligns with user intent and can be tracked, reasoned over, and verified.
+
+**Core Features:**
+
+* **Two-stage Reasoning Loop** (State Machine):
+
+  * **Stage 1:** Capture client intent, map to AI code action.
+  * **Stage 2:** Validate AI-generated code, detect misalignment, log corrections.
+* **Hook System Integration**:
+
+  * Identify injection points in **Roo Code** for tracking.
+  * Pre-commit, post-commit, and runtime hooks for tracing execution.
+* **`.orchestration/` directory**:
+
+  * Stores intent metadata, execution logs, and reasoning states.
+* **Intent-Code Mapping**:
+
+  * Links user intent → AI agent decisions → generated code → execution results.
+* **Auditability**:
+
+  * Every code change is traceable to its originating intent.
+
+---
+
+## **2. Architecture Layers**
+
+### **A. Input Layer (Intent Capture)**
+
+* **Source:** User commands in the IDE, chat prompts, or code requests.
+* **Components:**
+
+  * Intent Parser (NLP model / regex-based)
+  * Preprocessing Engine (normalize ambiguous input)
+* **Output:** Structured intent objects (`JSON/YAML`).
+
+### **B. Hook System Layer**
+
+* **Integration Points:** Roo Code Extension
+
+  * **Pre-commit hook:** Captures intent vs proposed AI code.
+  * **Post-commit hook:** Logs executed code and execution result.
+  * **Custom Reasoning hooks:** Intercepts AI agent output for validation.
+* **Responsibilities:**
+
+  * Validate AI output before commit.
+  * Trigger state updates in Reasoning Loop.
+  * Maintain orchestration logs.
+
+### **C. Orchestration & Reasoning Layer**
+
+* **State Machine (Two-Stage Loop)**:
+
+  * **Stage 1: Intent → Proposed Code**
+
+    * AI agent generates code based on captured intent.
+    * Hook system verifies structure and alignment.
+  * **Stage 2: Code Validation**
+
+    * Execute test cases or lint checks.
+    * Detect mismatches and suggest corrections.
+* **Data Storage:** `.orchestration/` directory
+
+  * Stores:
+
+    * Intent metadata
+    * AI decisions and reasoning traces
+    * Validation results
+    * Hook system logs
+
+### **D. Storage & Traceability Layer**
+
+* **File System:** `.orchestration/` for local tracking
+* **Optional DB:** Lightweight database (SQLite/PostgreSQL) for:
+
+  * Intent history
+  * AI agent output logs
+  * Validation state
+* **Purpose:** Allows historical analysis and auditability.
+
+### **E. Output & Feedback Layer**
+
+* **Developer Feedback:**
+
+  * Misalignment alerts
+  * Suggested corrections
+  * Intent-Code mapping visualizations
+* **Metrics & Analysis:**
+
+  * Traceability coverage
+  * Reasoning loop success rate
+  * Hook system performance
+
+---
+
+## **3. Development Plan / Workflow**
+
+1. **Phase 0: Prep**
+
+   * Review `ARCHITECTURE-NOTES.md` for Roo Code injection points.
+   * Map the cognitive and trust debt decisions → reasoning logic.
+   * Setup Git repo with **Git Speck Kit**.
+
+2. **Phase 1: Hook System Implementation**
+
+   * Identify Roo Code extension points for:
+
+     * pre-commit
+     * post-commit
+     * runtime reasoning interception
+   * Build hook scripts.
+   * Unit test hooks independently.
+
+3. **Phase 2: Reasoning Loop**
+
+   * Implement two-stage state machine.
+   * Connect hooks to Reasoning Loop states.
+   * Implement intent validation logic.
+
+4. **Phase 3: Orchestration Directory**
+
+   * `.orchestration/` for:
+
+     * intent.json
+     * reasoning_state.json
+     * validation_results.json
+   * Implement read/write APIs for traceability.
+
+5. **Phase 4: Logging & Traceability**
+
+   * Implement audit logs for every hook event.
+   * Integrate with Git Speck Kit for code snapshots.
+   * Enable metrics collection for AI alignment tracking.
+
+6. **Phase 5: Testing & Validation**
+
+   * Create sample AI-generated code scenarios.
+   * Test traceability pipeline end-to-end.
+   * Measure coverage of intent-code alignment.
+
+7. **Phase 6: Documentation**
+
+   * Maintain `ARCHITECTURE_NOTES.md` and `README.md`.
+   * Document hook usage, state machine, and orchestration structure.
+
+---
+
+## **4. Tech Stack / Tools**
+
+* **Git & Git Speck Kit:** Source control, snapshots, hooks.
+* **Python / Node.js:** For hooks and orchestration logic.
+* **JSON/YAML:** Intent and traceability storage.
+* **Roo Code Extension:** Injection points for hook system.
+* **Lightweight DB (Optional):** SQLite or PostgreSQL for logs.
+* **NLP / Parsing:** Optional intent parsing models.
+* **Testing Frameworks:** pytest / Jest for automated validation.
+
+---
+
+## **5. Key Architectural Decisions (From Cognitive & Trust Debt)**
+
+* Track only **AI-generated code relevant to intent** instead of all outputs.
+* Enforce **two-stage validation loop** to prevent drift between intent and code.
+* Maintain **self-contained orchestration directory** to simplify tracing and rollback.
+* Use **hooks as checkpoints** rather than full code reviews to scale traceability.
+* **Metrics-driven design:** Log reasoning steps to improve future AI alignment.