Fresh start - excluded large ROM JSON files

skills/memory-worker/SKILL.md

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+# Memory Worker Skill
+
+Version: 2.0 (2026-03-01 Update)
+
+## Purpose
+Extract important information from daily notes and store it in structured SQLite database.
+
+## CRITICAL: Schema Correction (2026.2.26+ Security)
+
+The generated script MUST have correct SQLite schema. Check for these issues:
+
+### FIXED Schema for memory_cells
+**7 columns including updated_at:**
+```python
+cursor.execute('''
+    CREATE TABLE IF NOT EXISTS memory_cells (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        scene TEXT,
+        cell_type TEXT,
+        salience INTEGER,
+        content TEXT,
+        source_file TEXT,
+        created_at TEXT,
+        updated_at TEXT DEFAULT CURRENT_TIMESTAMP
+    )
+''')
+```
+
+**INSERT must include all 7 columns:**
+```python
+cursor.execute('''
+    INSERT INTO memory_cells (scene, cell_type, salience, content, source_file, created_at, updated_at)
+    VALUES (?, ?, ?, ?, ?, ?, ?)
+''', (scene, cell_type, salience, content, source_file, timestamp, timestamp))
+```
+
+### FIXED Schema for scenes
+**6 columns including high_salience_count:**
+```python
+cursor.execute('''
+    CREATE TABLE IF NOT EXISTS scenes (
+        scene TEXT PRIMARY KEY,
+        summary TEXT,
+        item_count INTEGER DEFAULT 0,
+        high_salience_count INTEGER DEFAULT 0,
+        created_at TEXT,
+        updated_at TEXT DEFAULT CURRENT_TIMESTAMP
+    )
+''')
+```
+
+**INSERT/UPDATE must include high_salience_count:**
+```python
+cursor.execute('''
+    INSERT OR REPLACE INTO scenes (scene, summary, item_count, high_salience_count, created_at, updated_at)
+    VALUES (?, ?, ?, ?, ?, ?)
+''', (scene, summary, count, high_salience, timestamp, timestamp))
+```
+
+### FIXED Icon Characters (No Unicode Emoji)
+Use simple characters, not emojis:
+- Task: `[x]` not `✅`
+- Maintenance: `[w]` not `🔧`
+- Heartbeat: `[h]` not `💓`
+- Note: `[n]` not `📝`
+
+## Updated Template
+```python
+#!/usr/bin/env python3
+import sqlite3
+import os
+from datetime import datetime
+
+# Configuration
+DB_PATH = os.path.expanduser("~/.openclaw/memory.db")
+SOURCE_FILE = "YYYY-MM-DD.md"
+SCENE = "YYYY-MM-DD"
+
+def init_db():
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    
+    # FIXED: Include updated_at column
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS memory_cells (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            scene TEXT,
+            cell_type TEXT,
+            salience INTEGER,
+            content TEXT,
+            source_file TEXT,
+            created_at TEXT,
+            updated_at TEXT DEFAULT CURRENT_TIMESTAMP
+        )
+    ''')
+    
+    # FIXED: Include high_salience_count column
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS scenes (
+            scene TEXT PRIMARY KEY,
+            summary TEXT,
+            item_count INTEGER DEFAULT 0,
+            high_salience_count INTEGER DEFAULT 0,
+            created_at TEXT,
+            updated_at TEXT DEFAULT CURRENT_TIMESTAMP
+        )
+    ''')
+    
+    conn.commit()
+    return conn
+
+def insert_cells(conn):
+    cursor = conn.cursor()
+    timestamp = datetime.now().isoformat()
+    
+    # Extract cells from daily note
+    cells = [
+        (SCENE, 'task', 5, 'High priority task description...'),
+        (SCENE, 'maintenance', 4, 'Maintenance activity description...'),
+        # ... more cells
+    ]
+    
+    count = 0
+    for scene, cell_type, salience, content in cells:
+        # FIXED: Include updated_at column
+        cursor.execute('''
+            INSERT INTO memory_cells (scene, cell_type, salience, content, source_file, created_at, updated_at)
+            VALUES (?, ?, ?, ?, ?, ?, ?)
+        ''', (scene, cell_type, salience, content, SOURCE_FILE, timestamp, timestamp))
+        count += 1
+    
+    high_salience = sum(1 for _, _, salience, _ in cells if salience >= 4)
+    summary = 'Generated scene summary'
+    
+    # FIXED: Include high_salience_count
+    cursor.execute('''
+        INSERT OR REPLACE INTO scenes (scene, summary, item_count, high_salience_count, created_at, updated_at)
+        VALUES (?, ?, ?, ?, ?, ?)
+    ''', (SCENE, summary, count, high_salience, timestamp, timestamp))
+    
+    conn.commit()
+    return count
+
+def generate_report(conn):
+    cursor = conn.cursor()
+    
+    cursor.execute('SELECT cell_type, COUNT(*) FROM memory_cells WHERE source_file = ? GROUP BY cell_type', (SOURCE_FILE,))
+    type_counts = cursor.fetchall()
+    
+    cursor.execute('SELECT COUNT(*) FROM memory_cells')
+    total = cursor.fetchone()[0]
+    
+    cursor.execute('SELECT summary FROM scenes WHERE scene = ?', (SCENE,))
+    summary = cursor.fetchone()
+    
+    # FIXED: No Unicode emojis
+    icons = {'task': '[x]', 'maintenance': '[w]', 'heartbeat': '[h]', 'note': '[n]'}
+    
+    report = f"""[Memory Worker Daily] - {SCENE}\n\n**Files Processed:** {SOURCE_FILE}\n"""
+    for cell_type, cnt in type_counts:
+        icon = icons.get(cell_type, '[*]')
+        report += f"{icon} {cell_type}: {cnt}\n"
+    
+    report += f"\n**Summary:**\n{summary[0] if summary else 'N/A'}\n\n**Total:** {total} cells"
+    return report
+
+def main():
+    conn = init_db()
+    count = insert_cells(conn)
+    report = generate_report(conn)
+    conn.close()
+    print(report)
+    print(f"Successfully inserted {count} cells")
+
+if __name__ == "__main__":
+    main()
+```
+
+## Testing
+Before generating:
+1. Verify schema columns match table creation
+2. Verify INSERT contains all columns
+3. Verify no Unicode emojis
+4. Test run locally before committing
+
+## History
+- 2026-03-01: Fixed schema mismatch (added updated_at and high_salience_count columns)
+- 2026-02-20: Initial version