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>
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daymade
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transcript-fixer/scripts/core/schema.sql
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transcript-fixer/scripts/core/schema.sql
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-- Transcript Fixer Database Schema v2.0
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-- Migration from JSON to SQLite for ACID compliance and scalability
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-- Author: ISTJ Chief Engineer
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-- Date: 2025-01-28
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-- Enable foreign keys
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PRAGMA foreign_keys = ON;
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-- Table: corrections
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-- Stores all correction mappings with metadata
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CREATE TABLE IF NOT EXISTS corrections (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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from_text TEXT NOT NULL,
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to_text TEXT NOT NULL,
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domain TEXT NOT NULL DEFAULT 'general',
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source TEXT NOT NULL CHECK(source IN ('manual', 'learned', 'imported')),
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confidence REAL NOT NULL DEFAULT 1.0 CHECK(confidence >= 0.0 AND confidence <= 1.0),
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added_by TEXT,
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added_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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usage_count INTEGER NOT NULL DEFAULT 0 CHECK(usage_count >= 0),
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last_used TIMESTAMP,
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notes TEXT,
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is_active BOOLEAN NOT NULL DEFAULT 1,
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UNIQUE(from_text, domain)
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);
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CREATE INDEX IF NOT EXISTS idx_corrections_domain ON corrections(domain);
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CREATE INDEX IF NOT EXISTS idx_corrections_source ON corrections(source);
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CREATE INDEX IF NOT EXISTS idx_corrections_added_at ON corrections(added_at);
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CREATE INDEX IF NOT EXISTS idx_corrections_is_active ON corrections(is_active);
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CREATE INDEX IF NOT EXISTS idx_corrections_from_text ON corrections(from_text);
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-- Table: context_rules
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-- Regex-based context-aware correction rules
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CREATE TABLE IF NOT EXISTS context_rules (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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pattern TEXT NOT NULL UNIQUE,
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replacement TEXT NOT NULL,
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description TEXT,
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priority INTEGER NOT NULL DEFAULT 0,
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is_active BOOLEAN NOT NULL DEFAULT 1,
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added_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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added_by TEXT
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);
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CREATE INDEX IF NOT EXISTS idx_context_rules_priority ON context_rules(priority DESC);
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CREATE INDEX IF NOT EXISTS idx_context_rules_is_active ON context_rules(is_active);
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-- Table: correction_history
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-- Audit log for all correction runs
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CREATE TABLE IF NOT EXISTS correction_history (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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filename TEXT NOT NULL,
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domain TEXT NOT NULL,
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run_timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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original_length INTEGER NOT NULL CHECK(original_length >= 0),
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stage1_changes INTEGER NOT NULL DEFAULT 0 CHECK(stage1_changes >= 0),
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stage2_changes INTEGER NOT NULL DEFAULT 0 CHECK(stage2_changes >= 0),
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model TEXT,
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execution_time_ms INTEGER CHECK(execution_time_ms >= 0),
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success BOOLEAN NOT NULL DEFAULT 1,
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error_message TEXT
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);
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CREATE INDEX IF NOT EXISTS idx_history_run_timestamp ON correction_history(run_timestamp DESC);
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CREATE INDEX IF NOT EXISTS idx_history_domain ON correction_history(domain);
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CREATE INDEX IF NOT EXISTS idx_history_success ON correction_history(success);
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-- Table: correction_changes
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-- Detailed changes made in each correction run
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CREATE TABLE IF NOT EXISTS correction_changes (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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history_id INTEGER NOT NULL,
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line_number INTEGER,
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from_text TEXT NOT NULL,
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to_text TEXT NOT NULL,
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rule_type TEXT NOT NULL CHECK(rule_type IN ('context', 'dictionary', 'ai')),
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rule_id INTEGER,
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context_before TEXT,
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context_after TEXT,
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FOREIGN KEY (history_id) REFERENCES correction_history(id) ON DELETE CASCADE
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);
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CREATE INDEX IF NOT EXISTS idx_changes_history_id ON correction_changes(history_id);
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CREATE INDEX IF NOT EXISTS idx_changes_rule_type ON correction_changes(rule_type);
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-- Table: learned_suggestions
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-- AI-learned patterns pending user review
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CREATE TABLE IF NOT EXISTS learned_suggestions (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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from_text TEXT NOT NULL,
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to_text TEXT NOT NULL,
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domain TEXT NOT NULL DEFAULT 'general',
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frequency INTEGER NOT NULL DEFAULT 1 CHECK(frequency > 0),
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confidence REAL NOT NULL CHECK(confidence >= 0.0 AND confidence <= 1.0),
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first_seen TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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last_seen TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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status TEXT NOT NULL DEFAULT 'pending' CHECK(status IN ('pending', 'approved', 'rejected')),
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reviewed_at TIMESTAMP,
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reviewed_by TEXT,
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UNIQUE(from_text, to_text, domain)
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);
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CREATE INDEX IF NOT EXISTS idx_suggestions_status ON learned_suggestions(status);
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CREATE INDEX IF NOT EXISTS idx_suggestions_domain ON learned_suggestions(domain);
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CREATE INDEX IF NOT EXISTS idx_suggestions_confidence ON learned_suggestions(confidence DESC);
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CREATE INDEX IF NOT EXISTS idx_suggestions_frequency ON learned_suggestions(frequency DESC);
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-- Table: suggestion_examples
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-- Example occurrences of learned patterns
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CREATE TABLE IF NOT EXISTS suggestion_examples (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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suggestion_id INTEGER NOT NULL,
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filename TEXT NOT NULL,
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line_number INTEGER,
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context TEXT NOT NULL,
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occurred_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (suggestion_id) REFERENCES learned_suggestions(id) ON DELETE CASCADE
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);
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CREATE INDEX IF NOT EXISTS idx_examples_suggestion_id ON suggestion_examples(suggestion_id);
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-- Table: system_config
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-- System configuration and preferences
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CREATE TABLE IF NOT EXISTS system_config (
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key TEXT PRIMARY KEY,
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value TEXT NOT NULL,
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value_type TEXT NOT NULL CHECK(value_type IN ('string', 'int', 'float', 'boolean', 'json')),
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description TEXT,
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updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
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);
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-- Insert default configuration
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INSERT OR IGNORE INTO system_config (key, value, value_type, description) VALUES
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('schema_version', '2.0', 'string', 'Database schema version'),
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('api_provider', 'GLM', 'string', 'API provider name'),
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('api_model', 'GLM-4.6', 'string', 'Default AI model'),
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('api_base_url', 'https://open.bigmodel.cn/api/anthropic', 'string', 'API endpoint URL'),
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('default_domain', 'general', 'string', 'Default correction domain'),
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('auto_learn_enabled', 'true', 'boolean', 'Enable automatic pattern learning'),
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('backup_enabled', 'true', 'boolean', 'Create backups before operations'),
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('learning_frequency_threshold', '3', 'int', 'Min frequency for learned suggestions'),
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('learning_confidence_threshold', '0.8', 'float', 'Min confidence for learned suggestions'),
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('history_retention_days', '90', 'int', 'Days to retain correction history'),
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('max_correction_length', '1000', 'int', 'Maximum length for correction text');
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-- Table: audit_log
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-- Comprehensive audit trail for all operations
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CREATE TABLE IF NOT EXISTS audit_log (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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action TEXT NOT NULL,
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entity_type TEXT NOT NULL,
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entity_id INTEGER,
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user TEXT,
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details TEXT,
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success BOOLEAN NOT NULL DEFAULT 1,
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error_message TEXT
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);
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CREATE INDEX IF NOT EXISTS idx_audit_timestamp ON audit_log(timestamp DESC);
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CREATE INDEX IF NOT EXISTS idx_audit_action ON audit_log(action);
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CREATE INDEX IF NOT EXISTS idx_audit_entity_type ON audit_log(entity_type);
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CREATE INDEX IF NOT EXISTS idx_audit_success ON audit_log(success);
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-- View: active_corrections
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-- Quick access to active corrections
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CREATE VIEW IF NOT EXISTS active_corrections AS
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SELECT
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id,
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from_text,
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to_text,
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domain,
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source,
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confidence,
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usage_count,
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last_used,
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added_at
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FROM corrections
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WHERE is_active = 1
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ORDER BY domain, from_text;
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-- View: pending_suggestions
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-- Quick access to suggestions pending review
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CREATE VIEW IF NOT EXISTS pending_suggestions AS
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SELECT
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s.id,
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s.from_text,
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s.to_text,
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s.domain,
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s.frequency,
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s.confidence,
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s.first_seen,
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s.last_seen,
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COUNT(e.id) as example_count
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FROM learned_suggestions s
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LEFT JOIN suggestion_examples e ON s.id = e.suggestion_id
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WHERE s.status = 'pending'
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GROUP BY s.id
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ORDER BY s.confidence DESC, s.frequency DESC;
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-- View: correction_statistics
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-- Statistics per domain
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CREATE VIEW IF NOT EXISTS correction_statistics AS
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SELECT
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domain,
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COUNT(*) as total_corrections,
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COUNT(CASE WHEN source = 'manual' THEN 1 END) as manual_count,
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COUNT(CASE WHEN source = 'learned' THEN 1 END) as learned_count,
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COUNT(CASE WHEN source = 'imported' THEN 1 END) as imported_count,
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SUM(usage_count) as total_usage,
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MAX(added_at) as last_updated
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FROM corrections
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WHERE is_active = 1
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GROUP BY domain;
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