SchemaGen has 12 tools with basic schemas and descriptions, but significant quality gaps prevent production use. All tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization) and input schemas are present but minimal. Critical issues: (1) SQL injection vulnerability, table_name, column_name, and old_name parameters are interpolated directly into SQL without sanitization, violating pattern:tool-gateway. (2) No error handling guidance, tools return raw SQL or status strings without recovery hints. (3) Parameter descriptions lack constraints, 'columns' in create_table is 'Dictionary mapping column names to their SQLite types' but doesn't specify valid SQLite types or format. (4) Output schemas undocumented, get_records returns 'List[Dict]' but LLMs don't know field names or types. (5) No idempotency guarantees, insert_record and create_table use 'IF NOT EXISTS' but don't document retry behavior. (6) Destructive operations (drop_table, delete_record, drop_column) lack confirmation or dry-run patterns. Average tool description length is ~35 chars (baseline 194 chars); descriptions are too terse for LLM selection.

• Sanitize all table_name, column_name, and identifier parameters using parameterized queries or identifier escaping (e.g., sqlite3.escape_identifier or a whitelist of valid names matching [a-zA-Z_][a-zA-Z0-9_]*). Never interpolate identifiers into SQL strings.
• Add a 'dry_run' parameter to destructive tools (drop_table, delete_record, drop_column) that returns the SQL that would be executed without committing. Require explicit confirmation for actual execution, or implement a separate 'confirm_drop_table' tool.
• Expand parameter descriptions with explicit constraints: 'columns: Dict[str, str] where keys are column names (alphanumeric + underscore) and values are SQLite types (TEXT, INTEGER, REAL, BLOB, NULL). Example: {"id": "INTEGER", "name": "TEXT"}'. Add similar constraints to all identifier parameters.
• Document output schemas in tool definitions. For get_records, specify: 'Returns List[Dict[str, Any]] where each dict represents a row with column names as keys and values matching the column types defined at table creation.' For create_table, specify: 'Returns {"status": "success"|"error", "table": str, "columns": Dict[str, str], "sql": str}'.
• Add error handling with recovery guidance. If create_table fails because the table exists, return '{"status": "error", "message": "Table already exists. Call get_schema() to inspect it, or use drop_table() first if you want to recreate it."}'. If get_records fails because the table doesn't exist, return '{"status": "error", "message": "Table not found. Call get_schema() to see available tables."}'.