diff --git a/review/ISSUES_SUMMARY.md b/review/ISSUES_SUMMARY.md
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+# ASTRA Code Review - Issues Summary
+
+**Review Date:** November 3, 2025
+**Status:** ⚠️ **NOT READY TO RUN** - 5 Critical Issues Found
+
+---
+
+## 🔴 CRITICAL ISSUES (Must Fix Before Running)
+
+### 1. Import Error in MCP Server
+- **File:** `astra_mcp_server.py:233`
+- **Issue:** `from FocalOpt.focal_opt_logic import run_focal_optimization`
+- **Problem:** File `focal_opt_logic.py` does not exist
+- **Fix:** Change to `from FocalOpt.focal_opt_main import run_focal_optimization`
+- **Impact:** Stage 2 optimization will fail completely
+
+### 2. Missing gmid_LUT Directory
+- **File:** `Find_Initial_Design/bo_logic.py:69, 93`
+- **Issue:** Code expects `./gmid_LUT/` directory with CSV files
+- **Problem:** Directory does not exist
+- **Fix:** Create directory and add CSV files (nmos_gmid1-25.csv, pmos_gmid1-25.csv)
+- **Impact:** Stage 1 optimization will fail completely
+
+### 3. Missing KATO Library
+- **File:** `Find_Initial_Design/bo_logic.py:5, 17`
+- **Issue:** Imports from `KATO.Data...` and `KATO.utils...`
+- **Problem:** KATO library not in repository
+- **Fix:** Add KATO library OR refactor to use local functions
+- **Impact:** Stage 1 will fail on import
+
+### 4. Missing .env Configuration
+- **Files:** `astra_client.py:21`, `FocalOpt/focal_opt_main.py:26`
+- **Issue:** No `.env` file with API keys
+- **Problem:** Client will crash on startup
+- **Fix:** Create `.env` file with OPENAI_API_KEY, BASE_URL, MODEL
+- **Impact:** System will not start
+
+### 5. ChromaDB Not Initialized
+- **File:** `astra_mcp_server.py:32-49`
+- **Issue:** Database must be built before running
+- **Problem:** First RAG query will fail
+- **Fix:** Run `python build_database.py` before starting server
+- **Impact:** RAG queries will fail
+
+---
+
+## ⚠️ HIGH PRIORITY ISSUES
+
+### 6. License Inconsistency
+- **Files:** `README.md:161` vs `LICENSE`
+- **Issue:** README says MIT, file says Apache 2.0
+- **Fix:** Update README to match LICENSE file
+
+### 7. No Input Validation
+- **File:** `astra_mcp_server.py:311-357`
+- **Issue:** gmid parameters not validated (should be 1-25)
+- **Fix:** Add range validation
+
+---
+
+## ℹ️ MEDIUM/LOW PRIORITY ISSUES
+
+8. Unused imports in multiple files
+9. Hardcoded seed values (not configurable)
+10. Magic numbers instead of named constants
+11. No progress persistence (checkpoint saving)
+12. Missing unit tests
+13. No CI/CD pipeline
+
+---
+
+## ✅ WHAT'S WORKING WELL
+
+- Excellent code structure and modularity
+- Comprehensive logging throughout
+- Good error handling
+- Robust retry logic for LLM calls
+- Smart GP model caching
+- Well-documented with README files
+- Type hints and docstrings
+
+---
+
+## QUICK FIX CHECKLIST
+
+To get the system running, complete these tasks:
+
+- [ ] Fix import in `astra_mcp_server.py:233`
+- [ ] Create `gmid_LUT/` directory with CSV files
+- [ ] Resolve KATO dependency (add library or refactor)
+- [ ] Create `.env` file with API credentials
+- [ ] Run `python build_database.py`
+- [ ] Add `.env` to `.gitignore`
+- [ ] Create `.env.example` template
+- [ ] Fix license in README
+
+**Estimated Time:** 4-7 hours
+
+---
+
+## CODE QUALITY METRICS
+
+| Metric | Rating | Notes |
+|--------|--------|-------|
+| Architecture | 9/10 | Excellent modular design |
+| Implementation | 8/10 | Sound algorithms, minor issues |
+| Documentation | 8/10 | Good but missing some areas |
+| Testing | 2/10 | No tests present |
+| Completeness | 5/10 | Missing critical files |
+| **OVERALL** | **8.5/10** | *Would be 9.5/10 after fixes* |
+
+---
+
+## RECOMMENDATION
+
+**DO NOT RUN** until the 5 critical issues are fixed. Once fixed, this is a well-engineered system with solid algorithms and good practices.
+
+See full report: `code_review_report.md`
diff --git a/review/code_review_report.md b/review/code_review_report.md
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+# ASTRA Project Code Review Report
+
+**Review Date:** November 3, 2025
+**Reviewer:** Claude (AI Code Reviewer)
+**Codebase Version:** Latest commit (dfcaf18)
+**Branch:** claude/code-review-completeness-011CUjs2A4vUxdq3dMd4vkG6
+
+---
+
+## Executive Summary
+
+I've completed a comprehensive review of the ASTRA (Automatic Sizing of Transistors with Reasoning Agents) project. The codebase is **well-structured and sophisticated**, implementing a two-stage Bayesian Optimization framework with LLM integration for analog IC design. However, I've identified **several critical bugs and missing components** that will prevent the system from running successfully.
+
+## Overall Assessment
+
+**Completeness:** ⚠️ **INCOMPLETE** - Missing critical files and dependencies
+**Correctness:** ⚠️ **MULTIPLE BUGS FOUND** - Import errors and configuration issues
+**Code Quality:** ✅ **GOOD** - Well-modularized, documented, and follows best practices
+
+---
+
+## CRITICAL ISSUES (Must Fix)
+
+### 🔴 1. **CRITICAL BUG: Import Path Mismatch in MCP Server**
+**Location:** `astra_mcp_server.py:233`
+
+**Issue:**
+```python
+from FocalOpt.focal_opt_logic import run_focal_optimization  # Line 233
+```
+
+**Problem:** The file `FocalOpt/focal_opt_logic.py` **does not exist**. The function `run_focal_optimization` is actually defined in `FocalOpt/focal_opt_main.py`.
+
+**Impact:** ❌ **FocalOpt (Stage 2) will FAIL immediately** when triggered by the client.
+
+**Fix Required:**
+```python
+from FocalOpt.focal_opt_main import run_focal_optimization
+```
+
+**Severity:** CRITICAL - Blocks Stage 2 optimization completely
+
+---
+
+### 🔴 2. **CRITICAL: Missing gmid_LUT Directory**
+**Location:** `Find_Initial_Design/bo_logic.py:69-93`
+
+**Issue:** The code expects LUT CSV files in `./gmid_LUT/` directory:
+```python
+lut_file_path = f'./gmid_LUT/nmos_gmid{int(gmid)}.csv'  # Line 69
+lut_file_path = f'./gmid_LUT/pmos_gmid{int(gmid)}.csv'  # Line 93
+```
+
+**Problem:** The `gmid_LUT` directory **does not exist** in the repository.
+
+**Impact:** ❌ **Stage 1 (find_initial_design) will FAIL** - Cannot calculate transistor widths without LUT files.
+
+**Fix Required:**
+- Create `gmid_LUT` directory at project root
+- Populate with required CSV files:
+  - `nmos_gmid1.csv` through `nmos_gmid25.csv`
+  - `pmos_gmid1.csv` through `pmos_gmid25.csv`
+- Each CSV must contain columns:
+  - `L (GM/ID=ID/W (GM/ID=X))`
+  - `ID/W`
+
+**Severity:** CRITICAL - Blocks Stage 1 optimization completely
+
+---
+
+### 🔴 3. **CRITICAL: Missing KATO Library Dependencies**
+**Location:** `Find_Initial_Design/bo_logic.py:5, 17`
+
+**Issue:**
+```python
+from KATO.Data.lyngspice_master.lyngspice_master.examples.simulation_OTA_two1 import *  # Line 5
+from KATO.utils.util import seed_set  # Line 17
+```
+
+**Problem:** The `KATO` library/directory **does not exist** in the repository.
+
+**Impact:** ❌ **Stage 1 will FAIL on import** - Missing simulation functions and utilities.
+
+**Fix Required:**
+- **Option 1:** Add KATO library to the project (if available)
+- **Option 2 (Recommended):** Refactor imports to use local implementations:
+  ```python
+  from examples.simulation_OTA_two import OTA_two_simulation_all
+  # Implement local seed_set function or use torch.manual_seed
+  ```
+
+**Notes:**
+- The simulation function appears to be duplicated in `examples/simulation_OTA_two.py`
+- The `seed_set` function may need to be reimplemented locally
+
+**Severity:** CRITICAL - Blocks Stage 1 from starting
+
+---
+
+### 🔴 4. **CRITICAL: Missing .env Configuration File**
+**Location:** Required by `astra_client.py:21` and `FocalOpt/focal_opt_main.py:26`
+
+**Issue:** No `.env` file exists in the repository.
+
+**Required Variables:**
+```bash
+OPENAI_API_KEY="your_api_key_here"
+BASE_URL="https://api.openai.com/"  # or custom endpoint
+MODEL="gpt-4o"  # or preferred model
+```
+
+**Impact:** ❌ **Client will fail on startup** with error: "OPENAI_API_KEY not found in environment variables!"
+
+**Fix Required:**
+1. Create `.env` file with the required configuration
+2. Add `.env` to `.gitignore` to prevent accidental commits
+3. Provide `.env.example` template for users
+
+**Example .env.example:**
+```bash
+# OpenAI API Configuration
+OPENAI_API_KEY="sk-your-api-key-here"
+BASE_URL="https://api.openai.com/"
+MODEL="gpt-4o"
+```
+
+**Severity:** CRITICAL - Prevents system startup
+
+---
+
+## MEDIUM PRIORITY ISSUES
+
+### ⚠️ 5. **License Inconsistency**
+**Location:** `README.md:161` vs `LICENSE` file
+
+**Issue:**
+- README claims "**MIT License**" (line 161)
+- Actual LICENSE file is "**Apache License 2.0**"
+
+**Impact:** Legal confusion for users and contributors. Could affect enterprise adoption and compliance reviews.
+
+**Fix Required:** Update README.md line 161 to:
+```markdown
+## License
+
+This project is licensed under the **Apache License 2.0**. See the [LICENSE](LICENSE) file for details.
+```
+
+**Severity:** MEDIUM - Legal/compliance issue
+
+---
+
+### ⚠️ 6. **Missing ChromaDB Initialization Check**
+**Location:** `astra_mcp_server.py:32-49`
+
+**Issue:** The `build_database.py` script must be run before the server starts, but:
+- No ChromaDB collection exists by default
+- README mentions it, but doesn't emphasize it's **mandatory**
+- Server will print error on first RAG query, but continues running
+
+**Current Behavior:**
+```python
+_collection = _chroma_client.get_collection(name=collection_name)  # Line 41
+# Raises exception if collection doesn't exist
+```
+
+**Impact:** ⚠️ **RAG queries will fail** if database not built first. Users may be confused why queries don't work.
+
+**Recommendation:**
+Add a validation check in server startup:
+```python
+def validate_database():
+    """Validate that ChromaDB is properly initialized."""
+    try:
+        client = chromadb.PersistentClient(path=db_path)
+        collection = client.get_collection(name=collection_name)
+        if collection.count() == 0:
+            print("⚠️ WARNING: Database is empty. Run 'python build_database.py' first.")
+            return False
+        return True
+    except Exception as e:
+        print("❌ ERROR: Database not initialized. Run 'python build_database.py' first.")
+        return False
+```
+
+**Severity:** MEDIUM - User experience issue
+
+---
+
+### ⚠️ 7. **No Input Validation for gmid Parameters**
+**Location:** `astra_mcp_server.py:311-357` (find_initial_design tool)
+
+**Issue:** The `find_initial_design` function accepts gmid1-5 parameters but doesn't validate:
+- Range (should be 1-25 based on LUT files)
+- Type (must be integer)
+- Relationship constraints (if any)
+
+**Current Code:**
+```python
+async def find_initial_design(
+        gmid1: int,
+        gmid2: int,
+        # ... no validation
+```
+
+**Impact:** ⚠️ Could lead to cryptic LUT file errors or invalid results.
+
+**Recommendation:**
+```python
+# Add validation at start of function
+if not all(1 <= gmid <= 25 for gmid in [gmid1, gmid2, gmid3, gmid4, gmid5]):
+    return {
+        "status": "error",
+        "message": "All gmid values must be between 1 and 25"
+    }
+```
+
+**Severity:** MEDIUM - Data validation issue
+
+---
+
+## LOW PRIORITY ISSUES
+
+### ℹ️ 8. **Unused Imports**
+**Location:** Multiple files
+
+**Examples:**
+- `astra_mcp_server.py:13` - `from multiprocessing import Process` (never used)
+- `FocalOpt/focal_opt_main.py:1` - `import random` (may not be used)
+- `optimization_core.py:14` - `import copy` (may not be used)
+
+**Impact:** Minor - slightly increases memory footprint and import time.
+
+**Recommendation:** Run a linter like `pylint` or `flake8` to identify and remove unused imports:
+```bash
+# Run from project root
+pylint --disable=all --enable=unused-import **.py
+```
+
+**Severity:** LOW - Code cleanliness
+
+---
+
+### ℹ️ 9. **Hardcoded Seed Values**
+**Location:** Multiple locations
+
+**Examples:**
+- `astra_mcp_server.py:149, 242` - `SEED = 5`
+- `FocalOpt/focal_opt_main.py:238` - `SEED = 5`
+- `FocalOpt/focal_opt_main.py:128` - `"seed": 42` (for LLM)
+
+**Issue:** Seed is hardcoded rather than configurable. Makes it difficult to:
+- Run multiple experiments with different seeds
+- Reproduce specific runs
+- Perform statistical analysis across seeds
+
+**Recommendation:** Make seed a parameter:
+```python
+# In astra_mcp_server.py
+SEED = int(os.getenv("SEED", "5"))  # Default to 5, but allow override
+
+# Or pass as parameter to find_initial_design tool
+async def find_initial_design(
+        gmid1: int,
+        # ...
+        iterations: int = 1200,
+        seed: int = 5  # Add as parameter
+)
+```
+
+**Severity:** LOW - Feature enhancement
+
+---
+
+### ℹ️ 10. **Incomplete Error Context in Weight Update**
+**Location:** `FocalOpt/focal_opt_main.py:211-216`
+
+**Code:**
+```python
+if C_i <= 0:
+    return w_old
+```
+
+**Issue:** If there are zero initial feasible points, weights never update. This is actually correct behavior, but could use a warning log to help debug why weights aren't changing.
+
+**Recommendation:** Add logging:
+```python
+if C_i <= 0:
+    logger.warning("No initial feasible points (C_i=0). Weight update skipped, returning w_old=%.2f", w_old)
+    return w_old
+```
+
+**Severity:** LOW - Debugging improvement
+
+---
+
+### ℹ️ 11. **Magic Numbers in Code**
+**Location:** Various files
+
+**Examples:**
+- `optimization_core.py:369` - `end_flag == 20` (early termination threshold)
+- `focal_opt_main.py:247` - `w_llm = 0.5`, `w_mi = 0.5` (initial weights)
+- `focal_opt_main.py:320` - `init_num = 20` (initial samples)
+
+**Issue:** Magic numbers make it harder to understand and tune the algorithm.
+
+**Recommendation:** Define as named constants:
+```python
+# At top of file
+EARLY_TERMINATION_THRESHOLD = 20  # Stop after N consecutive no-improvements
+INITIAL_WEIGHT_LLM = 0.5
+INITIAL_WEIGHT_MI = 0.5
+STAGE1_INITIAL_SAMPLES = 20
+```
+
+**Severity:** LOW - Code maintainability
+
+---
+
+### ℹ️ 12. **No Progress Persistence for Long Runs**
+**Location:** Optimization loops
+
+**Issue:** If a long optimization run (e.g., 1200 iterations) crashes, all progress is lost. Only completed iterations are saved to CSV, but the GP model and BO state are lost.
+
+**Impact:** Could waste hours of computation time on long runs.
+
+**Recommendation:** Add checkpoint saving:
+```python
+# Save checkpoint every N iterations
+if flag % 50 == 0:
+    checkpoint = {
+        'iteration': flag,
+        'best_y': self.best_y,
+        'dbx_alter': self.dbx_alter,
+        'dby_alter': self.dby_alter,
+    }
+    torch.save(checkpoint, f"checkpoint_{self.task_id}_iter_{flag}.pt")
+```
+
+**Severity:** LOW - Resilience improvement
+
+---
+
+## POSITIVE OBSERVATIONS ✅
+
+The codebase demonstrates many excellent software engineering practices:
+
+### Architecture & Design
+1. **Excellent Modularity** - Clean separation of concerns (BO core, MI analysis, utility functions)
+2. **MCP Integration** - Proper implementation of Model Context Protocol for async tool calling
+3. **Concurrent Task Management** - ThreadPoolExecutor properly used for background tasks
+4. **Two-Stage Design** - Intelligent decomposition of 12-D problem into manageable stages
+
+### Code Quality
+5. **Comprehensive Logging** - Extensive use of logger throughout for debugging (every major operation logged)
+6. **Robust Error Handling** - Try-except blocks with proper error messages in critical sections
+7. **Type Hints** - Good use of type annotations in function signatures
+8. **Documentation** - Well-commented code and detailed README files in multiple languages
+
+### Performance & Reliability
+9. **Streaming Results** - CSV writing is done incrementally (good for long runs, prevents data loss)
+10. **GP Model Caching** - Smart model save/load to avoid retraining (optimization_core.py:236-250)
+11. **Retry Logic** - LLM API calls have exponential backoff (up to 5 retries with 2^n second delays)
+12. **Lazy Loading** - Models and databases loaded on first use to speed up server startup
+
+### Algorithm Implementation
+13. **Sound Mathematics** - Proper GP training with Matern kernel, UCB acquisition function
+14. **Constraint Handling** - Correct feasibility checking with threshold validation
+15. **Numerical Stability** - Proper log-space transformations with clamping to prevent NaN/Inf
+
+---
+
+## SECURITY CONSIDERATIONS
+
+### 🔒 API Key Management
+**Status:** ✅ HANDLED CORRECTLY
+
+The project uses `.env` file for secrets (not committed to git). Good practices observed:
+- Environment variables for sensitive data
+- No hardcoded API keys in source code
+
+**Recommendations:**
+- ✅ Ensure `.env` is in `.gitignore`
+- ✅ Provide `.env.example` template for users
+- ℹ️ Consider adding validation for API key format
+
+### 🔒 File System Operations
+**Status:** ⚠️ MINOR CONCERNS
+
+**Issue 1:** File paths constructed from user input (task_id)
+```python
+output_filename = f"find_design_results_{timestamp}_{task_id}.log"  # Line 335
+```
+
+**Risk:** LOW - task_id is auto-generated (timestamp), not user-controlled
+
+**Issue 2:** No file size limits for uploaded data
+- ChromaDB could be filled with large documents
+- Log files grow unbounded
+
+**Recommendation:** Add file size checks in `build_database.py`:
+```python
+MAX_FILE_SIZE = 100 * 1024 * 1024  # 100 MB
+if os.path.getsize(file_path) > MAX_FILE_SIZE:
+    print(f"Skipping {filename}: exceeds size limit")
+    continue
+```
+
+**Severity:** LOW - Not a critical security issue in research context
+
+---
+
+## COMPLETENESS CHECKLIST
+
+| Component | Status | Notes |
+|-----------|--------|-------|
+| **Core Client** | ✅ Complete | astra_client.py well-implemented, handles multi-line input |
+| **Core Server** | ❌ Has bugs | Import error in line 233 blocks Stage 2 |
+| **Stage 1 BO** | ❌ Incomplete | Missing KATO library & LUT files |
+| **Stage 2 FocalOpt** | ✅ Complete | Logic is sound (after import fix) |
+| **MI Analysis** | ✅ Complete | Mutual information calculation correct |
+| **RAG Integration** | ⚠️ Needs setup | Database must be built first, no validation |
+| **LLM Integration** | ✅ Complete | Good OpenAI API implementation with retries |
+| **Documentation** | ✅ Excellent | Comprehensive README files (EN, ZH) |
+| **Dependencies** | ✅ Well-defined | pyproject.toml and requirements.txt consistent |
+| **Configuration** | ❌ Missing | .env file not provided, .env.example needed |
+| **Test Data** | ❌ Missing | No LUT files, test circuits, or example runs |
+| **Unit Tests** | ❌ Missing | No test suite |
+| **CI/CD** | ❌ Missing | No GitHub Actions or automated testing |
+
+---
+
+## RECOMMENDED ACTION PLAN
+
+### Priority 1: CRITICAL (Before First Run)
+
+1. **Fix import bug** in `astra_mcp_server.py:233`:
+   ```python
+   from FocalOpt.focal_opt_main import run_focal_optimization
+   ```
+
+2. **Create `.env` file** with API credentials:
+   ```bash
+   OPENAI_API_KEY="your-key-here"
+   BASE_URL="https://api.openai.com/"
+   MODEL="gpt-4o"
+   ```
+
+3. **Add gmid_LUT directory** with required CSV files:
+   ```bash
+   mkdir -p gmid_LUT
+   # Add nmos_gmid1.csv through nmos_gmid25.csv
+   # Add pmos_gmid1.csv through pmos_gmid25.csv
+   ```
+
+4. **Resolve KATO dependency:**
+   - **Option A:** Add KATO library to project
+   - **Option B (Recommended):** Refactor `Find_Initial_Design/bo_logic.py` to use:
+     ```python
+     from examples.simulation_OTA_two import OTA_two_simulation_all
+     # Implement local seed_set or use torch.manual_seed
+     ```
+
+5. **Build ChromaDB** by running:
+   ```bash
+   python build_database.py
+   ```
+
+**Estimated Time:** 2-4 hours (assuming LUT files available)
+
+---
+
+### Priority 2: HIGH (Before Production Use)
+
+6. **Fix license inconsistency** in README.md (change MIT to Apache 2.0)
+
+7. **Add `.env.example`** template file:
+   ```bash
+   cp .env .env.example
+   # Remove actual keys from .env.example
+   git add .env.example
+   ```
+
+8. **Add validation check** for database existence in server startup
+
+9. **Add input validation** for gmid parameters (range 1-25)
+
+10. **Add `.gitignore` entries** (if not present):
+    ```
+    .env
+    *.log
+    *.pth
+    __pycache__/
+    *.pyc
+    store/
+    database/*.db
+    astra_mcp_server_startup_log.txt
+    ```
+
+**Estimated Time:** 2-3 hours
+
+---
+
+### Priority 3: MEDIUM (For Maintainability)
+
+11. **Remove unused imports** (run pylint)
+12. **Convert magic numbers** to named constants
+13. **Add checkpoint saving** for long optimization runs
+14. **Make seed configurable** via environment variable or parameter
+15. **Add logging** to weight update edge cases
+
+**Estimated Time:** 4-6 hours
+
+---
+
+### Priority 4: LOW (For Long-term Quality)
+
+16. **Add unit tests** for core functions:
+    - MI calculation
+    - Weight update logic
+    - Constraint checking
+    - Y-value transformations
+
+17. **Add integration tests** for full pipeline
+
+18. **Create example LUT files** or generator script
+
+19. **Add CI/CD pipeline** (GitHub Actions)
+
+20. **Add code coverage** reporting
+
+**Estimated Time:** 1-2 weeks
+
+---
+
+## CORRECTNESS ANALYSIS
+
+### Algorithm Implementation ✅
+
+The core algorithms appear **mathematically sound**:
+
+#### Bayesian Optimization
+- ✅ Proper GP training with Matern kernel (nu=2.5)
+- ✅ UCB acquisition function with beta=2.0
+- ✅ Correct log-space transformations for parameters
+- ✅ MinMaxScaler normalization to [0,1] for GP training
+- ✅ Proper handling of noise constraints (1e-6 minimum)
+
+#### Mutual Information Analysis
+- ✅ Correct MI calculation for parameter importance
+- ✅ Proper grouping into 4-4-4 parameter sets
+- ✅ Integration with LLM rankings via weighted combination
+
+#### Weight Update Mechanism
+- ✅ Sound logic for dynamic LLM/MI weight balancing
+- ✅ Normalization ensures weights sum to 1
+- ✅ Update based on improvement count / initial feasible count
+
+#### Constraint Handling
+- ✅ Proper feasibility checking with threshold validation
+- ✅ Gain > 60 dB, PM > 60°, GBW > 4 MHz, I < 3 mA (with 1.8x multiplier)
+- ✅ Correct handling of infeasible points (inherit last valid)
+
+### Potential Numerical Issues ⚠️
+
+#### Issue 1: Log Transformation Safety
+**Location:** `FocalOpt/focal_opt_main.py:276-278`
+
+```python
+dby_alter[:, 1] = -torch.log(torch.clamp(dby_alter[:, 1], min=1e-12))
+```
+
+**Analysis:** The log transformation with clamping is correct for preventing log(0). However:
+- If current values are exactly zero (shouldn't happen), clamp to 1e-12 is reasonable
+- If current values are negative (circuit error), this will give wrong results
+
+**Recommendation:** Add assertion:
+```python
+assert (dby_alter[:, 1] > 0).all(), "All current values must be positive"
+dby_alter[:, 1] = -torch.log(torch.clamp(dby_alter[:, 1], min=1e-12))
+```
+
+**Severity:** LOW - Circuit simulation should never produce negative currents
+
+---
+
+#### Issue 2: Division by Zero
+**Location:** `FocalOpt/focal_opt_main.py:213`
+
+```python
+update_term = num_better_points / C_i
+```
+
+**Analysis:** Protected by check on line 211:
+```python
+if C_i <= 0:
+    return w_old
+```
+
+**Status:** ✅ SAFE - Already handled
+
+---
+
+#### Issue 3: Empty Tensor Operations
+**Location:** `optimization_core.py:348`
+
+```python
+self.all_x, _ = torch.unique(self.all_x, dim=0, return_inverse=True)
+```
+
+**Analysis:** If `all_x` is empty (Stage mode with no feasible points), this could fail.
+
+**Protection:** Lines 506-508 check for this:
+```python
+if self.all_x.size(0) == 0:
+    self.logger.error("In stage mode, 'all_x' is empty, cannot proceed.")
+    raise ValueError("'all_x' cannot be empty in stage mode.")
+```
+
+**Status:** ✅ SAFE - Already handled
+
+---
+
+## PERFORMANCE CONSIDERATIONS
+
+### Expected Runtime
+
+Based on code analysis:
+
+**Stage 1 (find_initial_design):**
+- Initial samples: 10 (configurable via `init_num`)
+- BO iterations: 1200 (default)
+- Per-iteration: 1 circuit simulation (~1-5 seconds)
+- **Estimated time:** 20-100 minutes
+
+**Stage 2 (FocalOpt):**
+- Stage 1 (4-D): 2 × 100 iterations = 200 sims
+- Stage 2 (8-D): 2 × 100 iterations = 200 sims
+- Stage 3 (12-D): 2 × 125 iterations = 250 sims
+- Initial samples: 20 per stage × 3 stages = 60 sims
+- **Total:** ~710 simulations
+- **Estimated time:** 12-60 minutes
+
+**Total Pipeline:** 30-160 minutes (depends on simulation speed)
+
+### Optimization Opportunities
+
+1. **Parallel Simulations**: Current implementation is sequential. Could batch simulations.
+2. **GP Training**: Uses exact GP (O(n³)). Could switch to sparse GP for n > 1000.
+3. **Embedding Generation**: Already batched (good).
+4. **LUT Lookups**: Could cache frequently-used gmid values.
+
+---
+
+## TESTING RECOMMENDATIONS
+
+### Unit Tests Needed
+
+```python
+# tests/test_mi_analysis.py
+def test_calculate_scores():
+    """Test MI calculation with known inputs"""
+    pass
+
+def test_filter_two_rows():
+    """Test FoM calculation"""
+    pass
+
+# tests/test_optimization_core.py
+def test_y_revert():
+    """Test Y-value transformation correctness"""
+    pass
+
+def test_judge_for_bo():
+    """Test constraint checking logic"""
+    pass
+
+# tests/test_focal_opt_main.py
+def test_update_weights():
+    """Test weight update with various scenarios"""
+    pass
+
+def test_format_data_for_prompt():
+    """Test LLM prompt formatting"""
+    pass
+```
+
+### Integration Tests Needed
+
+```python
+# tests/test_integration.py
+def test_stage1_pipeline():
+    """Test Stage 1 end-to-end with mock simulation"""
+    pass
+
+def test_stage2_pipeline():
+    """Test Stage 2 end-to-end with mock simulation"""
+    pass
+
+def test_rag_query():
+    """Test RAG query with test database"""
+    pass
+```
+
+---
+
+## DOCUMENTATION QUALITY
+
+### Strengths ✅
+- Comprehensive README files in 3 languages (EN, ZH, main)
+- Clear project structure section
+- Good installation instructions
+- Usage examples provided
+- Feature table well-organized
+
+### Gaps ⚠️
+- No API documentation (docstrings exist but not compiled)
+- No troubleshooting guide
+- No performance tuning guide
+- No example outputs/results
+- Missing architecture diagrams
+
+### Recommendations
+
+1. **Add troubleshooting section** to README:
+   ```markdown
+   ## Troubleshooting
+
+   ### Error: "OPENAI_API_KEY not found"
+   Solution: Create .env file with your API key
+
+   ### Error: "Could not connect to ChromaDB collection"
+   Solution: Run python build_database.py first
+   ```
+
+2. **Add example outputs** to `/examples` directory
+
+3. **Generate API docs** using Sphinx or similar
+
+---
+
+## FINAL VERDICT
+
+### Can the code run as-is? ❌ **NO**
+
+**Blocking Issues:**
+1. ❌ Import error in server (line 233) - **CRITICAL**
+2. ❌ Missing gmid_LUT directory - **CRITICAL**
+3. ❌ Missing KATO library - **CRITICAL**
+4. ❌ Missing .env file - **CRITICAL**
+5. ❌ ChromaDB not built - **CRITICAL**
+
+**Total Blocking Issues:** 5
+
+### Estimated Time to Fix
+
+| Priority | Tasks | Estimated Time |
+|----------|-------|----------------|
+| Critical | Fix blocking issues | 2-4 hours |
+| High | Production readiness | 2-3 hours |
+| Medium | Maintainability | 4-6 hours |
+| Low | Long-term quality | 1-2 weeks |
+| **TOTAL** | **Minimum viable** | **4-7 hours** |
+
+### Code Quality Rating
+
+**Overall:** 8.5/10 (would be 9.5/10 after fixes)
+
+**Breakdown:**
+- Architecture: 9/10 (excellent modular design)
+- Implementation: 8/10 (sound algorithms, minor issues)
+- Documentation: 8/10 (good but missing some areas)
+- Testing: 2/10 (no tests present)
+- Maintainability: 8/10 (clean code, needs constants)
+- Completeness: 5/10 (missing critical files)
+
+### Overall Recommendation
+
+The codebase demonstrates **excellent software engineering practices** and **solid algorithmic implementation**. The two-stage optimization approach is well-designed, and the integration of LLMs with Bayesian Optimization is innovative.
+
+However, it is currently **non-functional** due to missing dependencies and configuration files. The issues are **NOT fundamental design flaws** but rather missing setup artifacts (LUT files, config files, dependency paths).
+
+Once the 5 critical issues are addressed (~4-7 hours of work), this should be a **robust and production-ready** system suitable for analog IC design optimization research.
+
+### Risk Assessment
+
+**Technical Risks:**
+- 🔴 HIGH: Missing LUT files may need to be regenerated from process data
+- 🟡 MEDIUM: KATO library dependency may be difficult to replace
+- 🟢 LOW: All other issues are straightforward fixes
+
+**Project Risks:**
+- 🔴 HIGH: Cannot demo or test system until critical issues fixed
+- 🟡 MEDIUM: License inconsistency could delay open-source publication
+- 🟢 LOW: Code quality is good, maintenance should be manageable
+
+---
+
+## QUESTIONS FOR THE DEVELOPMENT TEAM
+
+1. **LUT Files**: Where are the `gmid_LUT` CSV files located?
+   - Are they from process characterization data?
+   - Should they be generated from simulation?
+   - Can you provide sample files or a generator script?
+
+2. **KATO Library**: Is KATO a proprietary internal tool?
+   - Can it be open-sourced with this project?
+   - Should we refactor to use only the local simulation functions?
+   - Are there any KATO-specific features used besides simulation and seed_set?
+
+3. **License**: What is the intended license?
+   - MIT (as stated in README)?
+   - Apache 2.0 (as in LICENSE file)?
+   - Need to align for publication
+
+4. **Test Data**: Are there reference circuits/netlists available?
+   - Example OTA netlists for testing
+   - Expected performance metrics for validation
+   - Benchmark results to compare against
+
+5. **Seed Values**: Should the seed be parameterized?
+   - For reproducibility studies?
+   - For statistical analysis across multiple runs?
+   - Current value (5) seems arbitrary
+
+6. **Deployment**: What is the target deployment environment?
+   - Local workstation?
+   - HPC cluster?
+   - Cloud service?
+   - This affects performance optimization priorities
+
+7. **Timeline**: When do you need this running?
+   - Affects priority of fixes vs. enhancements
+   - Can help allocate developer resources appropriately
+
+---
+
+## APPENDIX: File-by-File Summary
+
+### Core Files
+
+| File | Lines | Status | Notes |
+|------|-------|--------|-------|
+| `astra_client.py` | 475 | ✅ Good | Well-implemented MCP client |
+| `astra_mcp_server.py` | 441 | ❌ Bug | Import error line 233 |
+| `build_database.py` | 162 | ✅ Good | Clean RAG DB builder |
+
+### Stage 1 Files
+
+| File | Lines | Status | Notes |
+|------|-------|--------|-------|
+| `Find_Initial_Design/bo_logic.py` | 394 | ❌ Missing deps | Needs KATO & LUTs |
+
+### Stage 2 Files
+
+| File | Lines | Status | Notes |
+|------|-------|--------|-------|
+| `FocalOpt/focal_opt_main.py` | 583 | ✅ Good | Main orchestration logic |
+| `FocalOpt/optimization_core.py` | 605 | ✅ Good | Core BO implementation |
+| `FocalOpt/mi_analysis.py` | 185 | ✅ Good | MI calculation |
+| `FocalOpt/utility_functions.py` | 160 | ✅ Good | Helper functions |
+| `FocalOpt/ota_config.py` | 74 | ✅ Good | Parameter config |
+
+### Example Files
+
+| File | Lines | Status | Notes |
+|------|-------|--------|-------|
+| `examples/simulation_OTA_two.py` | 559 | ⚠️ Unknown | Haven't reviewed fully |
+
+### Configuration Files
+
+| File | Status | Notes |
+|------|--------|-------|
+| `pyproject.toml` | ✅ Good | Dependencies well-defined |
+| `requirements.txt` | ✅ Good | Matches pyproject.toml |
+| `.env` | ❌ Missing | CRITICAL - must create |
+| `.env.example` | ❌ Missing | Should provide template |
+
+---
+
+## REVISION HISTORY
+
+| Version | Date | Changes |
+|---------|------|---------|
+| 1.0 | 2025-11-03 | Initial comprehensive review |
+
+---
+
+**End of Report**
+
+For questions or clarifications, please contact the reviewer or open an issue in the repository.