Release v1.8.0: Add transcript-fixer skill

## New Skill: transcript-fixer v1.0.0

Correct speech-to-text (ASR/STT) transcription errors through dictionary-based rules and AI-powered corrections with automatic pattern learning.

**Features:**
- Two-stage correction pipeline (dictionary + AI)
- Automatic pattern detection and learning
- Domain-specific dictionaries (general, embodied_ai, finance, medical)
- SQLite-based correction repository
- Team collaboration with import/export
- GLM API integration for AI corrections
- Cost optimization through dictionary promotion

**Use cases:**
- Correcting meeting notes, lecture recordings, or interview transcripts
- Fixing Chinese/English homophone errors and technical terminology
- Building domain-specific correction dictionaries
- Improving transcript accuracy through iterative learning

**Documentation:**
- Complete workflow guides in references/
- SQL query templates
- Troubleshooting guide
- Team collaboration patterns
- API setup instructions

**Marketplace updates:**
- Updated marketplace to v1.8.0
- Added transcript-fixer plugin (category: productivity)
- Updated README.md with skill description and use cases
- Updated CLAUDE.md with skill listing and counts

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

transcript-fixer/scripts/examples/bulk_import.py

@@ -0,0 +1,153 @@
+#!/usr/bin/env python3
+"""
+Example: Bulk Import Corrections to SQLite Database
+
+This script demonstrates how to import corrections from various sources
+into the transcript-fixer SQLite database.
+
+Usage:
+    uv run scripts/examples/bulk_import.py
+"""
+
+from pathlib import Path
+from core import CorrectionRepository, CorrectionService
+
+
+def import_from_dict():
+    """Example: Import corrections from Python dictionary"""
+
+    # Initialize service
+    db_path = Path.home() / ".transcript-fixer" / "corrections.db"
+    repository = CorrectionRepository(db_path)
+    service = CorrectionService(repository)
+
+    # Define corrections as dictionary
+    corrections_dict = {
+        "巨升智能": "具身智能",
+        "巨升": "具身",
+        "奇迹创坛": "奇绩创坛",
+        "火星营": "火星营",
+        "矩阵公司": "初创公司",
+        "股价": "框架",
+        "三观": "三关"
+    }
+
+    # Convert to list format for import
+    corrections_list = []
+    for from_text, to_text in corrections_dict.items():
+        corrections_list.append({
+            "from_text": from_text,
+            "to_text": to_text,
+            "domain": "embodied_ai",
+            "source": "imported",
+            "confidence": 1.0
+        })
+
+    # Import
+    inserted, updated, skipped = service.import_corrections(
+        corrections=corrections_list,
+        merge=True
+    )
+
+    print(f"✅ Import complete:")
+    print(f"   - Inserted: {inserted}")
+    print(f"   - Updated: {updated}")
+    print(f"   - Skipped: {skipped}")
+
+    service.close()
+
+
+def import_from_json_file():
+    """Example: Import from old JSON format file"""
+    import json
+
+    # Sample JSON structure (v1.0 format)
+    sample_json = {
+        "metadata": {
+            "version": "1.0",
+            "domains": ["embodied_ai"],
+        },
+        "corrections": {
+            "巨升智能": "具身智能",
+            "巨升": "具身",
+        }
+    }
+
+    # Initialize service
+    db_path = Path.home() / ".transcript-fixer" / "corrections.db"
+    repository = CorrectionRepository(db_path)
+    service = CorrectionService(repository)
+
+    # Convert JSON to import format
+    domain = sample_json["metadata"].get("domains", ["general"])[0]
+    corrections_list = []
+
+    for from_text, to_text in sample_json["corrections"].items():
+        corrections_list.append({
+            "from_text": from_text,
+            "to_text": to_text,
+            "domain": domain,
+            "source": "imported",
+            "confidence": 1.0
+        })
+
+    # Import
+    inserted, updated, skipped = service.import_corrections(
+        corrections=corrections_list,
+        merge=True
+    )
+
+    print(f"✅ JSON import complete:")
+    print(f"   - Inserted: {inserted}")
+    print(f"   - Updated: {updated}")
+    print(f"   - Skipped: {skipped}")
+
+    service.close()
+
+
+def add_context_rules():
+    """Example: Add context-aware regex rules directly"""
+
+    db_path = Path.home() / ".transcript-fixer" / "corrections.db"
+    repository = CorrectionRepository(db_path)
+
+    # Add context rules via SQL
+    with repository._transaction() as conn:
+        rules = [
+            ("巨升方向", "具身方向", "巨升→具身", 10),
+            ("巨升现在", "具身现在", "巨升→具身", 10),
+            ("近距离的去看", "近距离地去看", "的→地 副词修饰", 5),
+            ("近距离搏杀", "近距离搏杀", "这里的'近距离'是正确的", 5),
+        ]
+
+        for pattern, replacement, description, priority in rules:
+            conn.execute("""
+                INSERT OR IGNORE INTO context_rules
+                (pattern, replacement, description, priority)
+                VALUES (?, ?, ?, ?)
+            """, (pattern, replacement, description, priority))
+
+    print("✅ Context rules added successfully")
+    repository.close()
+
+
+if __name__ == "__main__":
+    print("Transcript-Fixer Bulk Import Examples\n")
+    print("=" * 60)
+
+    # Example 1: Import from dictionary
+    print("\n1. Importing from Python dictionary...")
+    import_from_dict()
+
+    # Example 2: Import from JSON file
+    print("\n2. Importing from JSON format...")
+    import_from_json_file()
+
+    # Example 3: Add context rules
+    print("\n3. Adding context rules...")
+    add_context_rules()
+
+    print("\n" + "=" * 60)
+    print("✅ All examples completed!")
+    print("\nVerify with:")
+    print("  sqlite3 ~/.transcript-fixer/corrections.db 'SELECT COUNT(*) FROM active_corrections;'")