handling-sf-data — Skillopedia

Salesforce Data Operations Expert (handling-sf-data) Use this skill when the user needs Salesforce data work : record CRUD, bulk import/export, test data generation, cleanup scripts, or data factory patterns for validating Apex, Flow, or integration behavior. When This Skill Owns the Task Use when the work involves: - CLI commands - record creation, update, delete, upsert, export, or tree import/export - realistic test data generation - bulk data operations and cleanup - Apex anonymous scripts for data seeding / rollback Delegate elsewhere when the user is: - writing SOQL only → querying-soql…

, '', content, flags=re.MULTILINE)\n # Remove multi-line comments\n content = re.sub(r'/\\*[\\s\\S]*?\\*/', '', content)\n return content\n\n def _has_where_clause(self, content: str) -> bool:\n \"\"\"Check if query has a WHERE clause.\"\"\"\n return bool(re.search(r'\\bWHERE\\b', content, re.IGNORECASE))\n\n def _has_limit(self, content: str) -> bool:\n \"\"\"Check if query has a LIMIT clause.\"\"\"\n return bool(re.search(r'\\bLIMIT\\s+\\d+', content, re.IGNORECASE))\n\n def _has_hardcoded_ids(self, content: str) -> bool:\n \"\"\"Check for hardcoded Salesforce IDs.\"\"\"\n # Salesforce IDs are 15 or 18 character alphanumeric\n # Starting with specific prefixes: 001 (Account), 003 (Contact), etc.\n id_pattern = r\"'[a-zA-Z0-9]{15}'\" # 15-char ID\n id_pattern_18 = r\"'[a-zA-Z0-9]{18}'\" # 18-char ID\n\n return bool(re.search(id_pattern, content) or re.search(id_pattern_18, content))\n\n def _uses_indexed_fields(self, content: str) -> bool:\n \"\"\"Check if WHERE clause uses indexed fields.\"\"\"\n # Extract WHERE clause\n where_match = re.search(r'\\bWHERE\\b(.*?)(?:\\bORDER\\b|\\bGROUP\\b|\\bLIMIT\\b|$)',\n content, re.IGNORECASE | re.DOTALL)\n if not where_match:\n return False\n\n where_clause = where_match.group(1)\n\n # Check for indexed fields\n for field in self.INDEXED_FIELDS:\n if re.search(rf'\\b{field}\\b', where_clause, re.IGNORECASE):\n return True\n\n return False\n\n def _has_subquery(self, content: str) -> bool:\n \"\"\"Check if query has subqueries.\"\"\"\n # Look for nested SELECT in parentheses\n return bool(re.search(r'\\(\\s*SELECT\\b', content, re.IGNORECASE))\n\n def _has_relationship(self, content: str) -> bool:\n \"\"\"Check if query uses relationship queries.\"\"\"\n # Look for dot notation (child-to-parent) or __r suffix\n return bool(re.search(r'\\w+\\.\\w+|__r\\.', content))\n\n def _validate_syntax(self, content: str) -> List[Dict[str, Any]]:\n \"\"\"Validate SOQL syntax and return issues.\"\"\"\n issues = []\n\n # Check for SELECT without FROM\n if re.search(r'\\bSELECT\\b', content, re.IGNORECASE):\n if not re.search(r'\\bFROM\\b', content, re.IGNORECASE):\n issues.append({\n 'severity': 'error',\n 'message': 'SELECT statement missing FROM clause'\n })\n\n # Check for invalid operators\n if re.search(r'==', content):\n issues.append({\n 'severity': 'error',\n 'message': 'Invalid operator \"==\" - use \"=\" in SOQL'\n })\n\n if re.search(r'!=\\s*null', content, re.IGNORECASE):\n pass # Valid\n elif re.search(r'\u003c>', content):\n issues.append({\n 'severity': 'warning',\n 'message': 'Consider using \"!=\" instead of \"\u003c>\" for consistency'\n })\n\n # Check for SELECT *\n if re.search(r'\\bSELECT\\s+\\*', content, re.IGNORECASE):\n issues.append({\n 'severity': 'error',\n 'message': 'SELECT * is not valid in SOQL - specify field names'\n })\n\n # Check for proper string quoting\n if re.search(r\"=\\s*\\\"[^\\\"]*\\\"\", content):\n issues.append({\n 'severity': 'warning',\n 'message': 'Use single quotes for string literals in SOQL'\n })\n\n # Check for unbalanced parentheses\n open_parens = content.count('(')\n close_parens = content.count(')')\n if open_parens != close_parens:\n issues.append({\n 'severity': 'error',\n 'message': f'Unbalanced parentheses: {open_parens} open, {close_parens} close'\n })\n\n # Check for TYPEOF without END\n if re.search(r'\\bTYPEOF\\b', content, re.IGNORECASE):\n if not re.search(r'\\bEND\\b', content, re.IGNORECASE):\n issues.append({\n 'severity': 'error',\n 'message': 'TYPEOF expression missing END keyword'\n })\n\n # Check for reserved words as field names (common issues)\n reserved = ['SELECT', 'FROM', 'WHERE', 'ORDER', 'GROUP', 'LIMIT']\n for word in reserved:\n # Look for patterns like \"SELECT SELECT\" or \"field, SELECT\"\n if re.search(rf'\\b{word}\\s*,|\\,\\s*{word}\\b', content, re.IGNORECASE):\n issues.append({\n 'severity': 'warning',\n 'message': f'Possible misuse of reserved word \"{word}\"'\n })\n\n return issues\n\n def get_query_complexity(self, content: str) -> Dict[str, int]:\n \"\"\"Analyze query complexity metrics.\"\"\"\n clean = self._remove_comments(content)\n\n return {\n 'select_fields': len(re.findall(r'\\bSELECT\\b.*?\\bFROM\\b', clean, re.IGNORECASE | re.DOTALL)),\n 'where_conditions': len(re.findall(r'\\b(AND|OR)\\b', clean, re.IGNORECASE)) + 1 if self._has_where_clause(clean) else 0,\n 'subqueries': len(re.findall(r'\\(\\s*SELECT\\b', clean, re.IGNORECASE)),\n 'joins': len(re.findall(r'__r\\.|\\.Name|\\.Id', clean)),\n 'aggregates': len(re.findall(r'\\b(COUNT|SUM|AVG|MIN|MAX)\\s*\\(', clean, re.IGNORECASE))\n }\n\n def suggest_optimizations(self, content: str) -> List[str]:\n \"\"\"Suggest query optimizations.\"\"\"\n suggestions = []\n clean = self._remove_comments(content)\n\n # Check for missing indexed field in WHERE\n if self._has_where_clause(clean) and not self._uses_indexed_fields(clean):\n suggestions.append('Add an indexed field (Id, Name, CreatedDate) to WHERE for better performance')\n\n # Check for ORDER BY without LIMIT\n if re.search(r'\\bORDER\\s+BY\\b', clean, re.IGNORECASE):\n if not self._has_limit(clean):\n suggestions.append('Consider adding LIMIT when using ORDER BY')\n\n # Check for SELECT with many fields\n select_match = re.search(r'\\bSELECT\\b(.*?)\\bFROM\\b', clean, re.IGNORECASE | re.DOTALL)\n if select_match:\n fields = select_match.group(1)\n field_count = len([f.strip() for f in fields.split(',') if f.strip()])\n if field_count > 20:\n suggestions.append(f'Query selects {field_count} fields - consider selecting only needed fields')\n\n # Check for deeply nested subqueries\n subquery_depth = len(re.findall(r'\\(\\s*SELECT\\b', clean, re.IGNORECASE))\n if subquery_depth > 2:\n suggestions.append('Consider simplifying query - deeply nested subqueries may impact performance')\n\n return suggestions\n\n\n# Standalone execution for testing\nif __name__ == '__main__':\n import sys\n\n if len(sys.argv) \u003c 2:\n print('Usage: python soql_validator.py \u003csoql_file>')\n sys.exit(1)\n\n with open(sys.argv[1], 'r') as f:\n content = f.read()\n\n validator = SOQLValidator(content)\n result = validator.validate()\n\n print('SOQL Validation Results:')\n print('=' * 40)\n for key, value in result.items():\n if key not in ['issues', 'recommendations']:\n print(f'{key}: {value}')\n\n if result['issues']:\n print('\\nIssues:')\n for issue in result['issues']:\n print(f\" [{issue['severity']}] {issue['message']}\")\n\n if result['recommendations']:\n print('\\nRecommendations:')\n for rec in result['recommendations']:\n print(f' - {rec}')\n","content_type":"text/x-python; charset=utf-8","language":"python","size":11201,"content_sha256":"035e4a3620b8e127532b610ab09efb1e270b22539150aef0e5aa053d2c6db887"},{"filename":"scripts/validate_data_operation.py","content":"#!/usr/bin/env python3\n\"\"\"\nsf-data Validation Module\n=========================\n\nValidates data operation files against the 130-point scoring system:\n- Query Efficiency (25 points)\n- Bulk Safety (25 points)\n- Data Integrity (20 points)\n- Security & FLS (20 points)\n- Test Patterns (15 points)\n- Cleanup & Isolation (15 points)\n- Documentation (10 points)\n\"\"\"\n\nimport re\nfrom pathlib import Path\nfrom typing import Dict, List, Any, Optional\n\nclass DataOperationValidator:\n \"\"\"Validates data operation files.\"\"\"\n\n # Scoring categories\n CATEGORIES = {\n 'query_efficiency': {\n 'name': 'Query Efficiency',\n 'max': 25,\n 'score': 25,\n 'issues': []\n },\n 'bulk_safety': {\n 'name': 'Bulk Safety',\n 'max': 25,\n 'score': 25,\n 'issues': []\n },\n 'data_integrity': {\n 'name': 'Data Integrity',\n 'max': 20,\n 'score': 20,\n 'issues': []\n },\n 'security_fls': {\n 'name': 'Security & FLS',\n 'max': 20,\n 'score': 20,\n 'issues': []\n },\n 'test_patterns': {\n 'name': 'Test Patterns',\n 'max': 15,\n 'score': 15,\n 'issues': []\n },\n 'cleanup_isolation': {\n 'name': 'Cleanup & Isolation',\n 'max': 15,\n 'score': 15,\n 'issues': []\n },\n 'documentation': {\n 'name': 'Documentation',\n 'max': 10,\n 'score': 10,\n 'issues': []\n }\n }\n\n def __init__(self, file_path: str):\n self.file_path = Path(file_path)\n self.content = ''\n self.file_type = ''\n self.issues: List[Dict[str, Any]] = []\n self.recommendations: List[str] = []\n self.categories = self._init_categories()\n\n def _init_categories(self) -> Dict[str, Dict[str, Any]]:\n \"\"\"Initialize fresh category scores.\"\"\"\n import copy\n return copy.deepcopy(self.CATEGORIES)\n\n def validate(self) -> Optional[Dict[str, Any]]:\n \"\"\"Run validation and return results.\"\"\"\n if not self.file_path.exists():\n return None\n\n try:\n with open(self.file_path, 'r', encoding='utf-8') as f:\n self.content = f.read()\n except Exception:\n return None\n\n # Determine file type\n self.file_type = self.file_path.suffix.lower()\n\n # Run type-specific validation\n if self.file_type == '.apex':\n self._validate_apex()\n elif self.file_type == '.soql':\n self._validate_soql()\n elif self.file_type == '.csv':\n self._validate_csv()\n elif self.file_type == '.json':\n self._validate_json()\n else:\n return None\n\n # Calculate total score\n total_score = sum(cat['score'] for cat in self.categories.values())\n max_score = sum(cat['max'] for cat in self.categories.values())\n\n return {\n 'score': total_score,\n 'max_score': max_score,\n 'categories': {cat['name']: {'score': cat['score'], 'max': cat['max']}\n for cat in self.categories.values()},\n 'issues': self.issues,\n 'recommendations': self.recommendations\n }\n\n def _validate_apex(self):\n \"\"\"Validate Apex data operation file.\"\"\"\n content = self.content\n\n # Query Efficiency (25 points)\n self._check_query_efficiency(content)\n\n # Bulk Safety (25 points)\n self._check_bulk_safety(content)\n\n # Data Integrity (20 points)\n self._check_data_integrity(content)\n\n # Security & FLS (20 points)\n self._check_security(content)\n\n # Test Patterns (15 points)\n self._check_test_patterns(content)\n\n # Cleanup & Isolation (15 points)\n self._check_cleanup(content)\n\n # Documentation (10 points)\n self._check_documentation(content)\n\n def _validate_soql(self):\n \"\"\"Validate SOQL query file.\"\"\"\n content = self.content\n\n # Import SOQL validator\n try:\n from soql_validator import SOQLValidator\n soql_validator = SOQLValidator(content)\n soql_result = soql_validator.validate()\n\n # Apply SOQL-specific scoring\n if soql_result.get('has_where_clause', False):\n pass # Good\n else:\n self._deduct('query_efficiency', 5, 'Missing WHERE clause')\n\n if soql_result.get('has_limit', False):\n pass # Good\n else:\n self._deduct('query_efficiency', 3, 'Missing LIMIT clause')\n\n if soql_result.get('has_hardcoded_ids', False):\n self._deduct('query_efficiency', 5, 'Hardcoded record IDs found')\n\n except ImportError:\n # Basic SOQL validation\n if 'WHERE' not in content.upper():\n self._deduct('query_efficiency', 5, 'Missing WHERE clause')\n if 'LIMIT' not in content.upper():\n self._deduct('query_efficiency', 3, 'Missing LIMIT clause')\n\n # Documentation check for SOQL\n if not content.strip().startswith('--'):\n self._deduct('documentation', 5, 'Missing SOQL documentation/comments')\n\n def _validate_csv(self):\n \"\"\"Validate CSV import file.\"\"\"\n lines = self.content.strip().split('\\n')\n\n if len(lines) \u003c 2:\n self._deduct('data_integrity', 10, 'CSV file has no data rows')\n return\n\n # Check for header row\n header = lines[0]\n if not header or ',' not in header:\n self._deduct('data_integrity', 5, 'CSV missing proper header row')\n\n # Check for consistent column count\n expected_cols = len(header.split(','))\n for i, line in enumerate(lines[1:], 2):\n if line.strip() and len(line.split(',')) != expected_cols:\n self._deduct('data_integrity', 2, f'Inconsistent column count on line {i}')\n break\n\n # Check for potential PII patterns\n self._check_csv_security(self.content)\n\n def _validate_json(self):\n \"\"\"Validate JSON tree import file.\"\"\"\n import json as json_lib\n\n try:\n data = json_lib.loads(self.content)\n except json_lib.JSONDecodeError as e:\n self._deduct('data_integrity', 20, f'Invalid JSON: {str(e)}')\n return\n\n # Check for proper sObject tree format\n if 'records' not in data:\n self._deduct('data_integrity', 10, 'Missing \"records\" array')\n return\n\n records = data.get('records', [])\n\n for i, record in enumerate(records):\n if 'attributes' not in record:\n self._deduct('data_integrity', 5, f'Record {i+1} missing \"attributes\"')\n else:\n attrs = record['attributes']\n if 'type' not in attrs:\n self._deduct('data_integrity', 3, f'Record {i+1} missing object type')\n if 'referenceId' not in attrs:\n self._deduct('data_integrity', 2, f'Record {i+1} missing referenceId')\n\n def _check_query_efficiency(self, content: str):\n \"\"\"Check for query efficiency issues.\"\"\"\n # Check for queries in loops\n if re.search(r'for\\s*\$[^)]*\$\\s*\\{[^}]*\\[SELECT', content, re.IGNORECASE | re.DOTALL):\n self._deduct('query_efficiency', 10, 'SOQL query inside for loop (N+1 pattern)')\n\n # Check for hardcoded IDs\n if re.search(r\"'[a-zA-Z0-9]{15,18}'\", content):\n self._deduct('query_efficiency', 5, 'Hardcoded Salesforce ID found')\n\n # Check for SELECT * equivalent (all fields)\n if re.search(r'SELECT\\s+\\*', content, re.IGNORECASE):\n self._deduct('query_efficiency', 5, 'SELECT * is not valid in SOQL')\n\n def _check_bulk_safety(self, content: str):\n \"\"\"Check for bulk safety issues.\"\"\"\n # Check for DML in loops\n dml_in_loop = re.search(\n r'for\\s*\$[^)]*\$\\s*\\{[^}]*(insert|update|delete|upsert)\\s+',\n content, re.IGNORECASE | re.DOTALL\n )\n if dml_in_loop:\n self._deduct('bulk_safety', 10, 'DML operation inside for loop')\n\n # Check for single-record operations when bulk would be better\n single_record_pattern = re.search(\n r'(insert|update|delete)\\s+\\w+\\s*;(?!\\s*//\\s*single)',\n content, re.IGNORECASE\n )\n # This is a soft check - single records are sometimes intentional\n\n # Check for list-based DML (good pattern)\n if re.search(r'(insert|update|delete)\\s+\\w+List', content, re.IGNORECASE):\n pass # Good - using list-based DML\n elif re.search(r'(insert|update|delete)\\s+new\\s+List\u003c', content, re.IGNORECASE):\n pass # Good - using list\n\n def _check_data_integrity(self, content: str):\n \"\"\"Check for data integrity issues.\"\"\"\n # Check for required field handling\n if 'required' in content.lower() or 'mandatory' in content.lower():\n pass # Awareness of required fields\n\n # Check for null checks\n if re.search(r'!=\\s*null|!= null', content):\n pass # Good - null checking\n\n def _check_security(self, content: str):\n \"\"\"Check for security issues.\"\"\"\n # Check for PII patterns\n pii_patterns = [\n (r'\\b\\d{3}-\\d{2}-\\d{4}\\b', 'SSN pattern detected'),\n (r'\\b\\d{4}[-\\s]?\\d{4}[-\\s]?\\d{4}[-\\s]?\\d{4}\\b', 'Credit card pattern detected'),\n (r'\\b[A-Za-z0-9._%+-]+@(gmail|yahoo|hotmail|outlook)\\.(com|net|org)\\b',\n 'Personal email domain in test data')\n ]\n\n for pattern, message in pii_patterns:\n if re.search(pattern, content):\n self._deduct('security_fls', 10, message)\n\n # Check for WITH USER_MODE usage (good practice)\n if 'WITH USER_MODE' in content.upper():\n pass # Good - respecting FLS\n\n def _check_test_patterns(self, content: str):\n \"\"\"Check for good test data patterns.\"\"\"\n # Check for bulk record creation (200+)\n bulk_patterns = [\n r'(\\d{3,})\\s*[;,)]', # Numbers 100+\n r'count\\s*[=:]\\s*(\\d{3,})',\n r'recordCount\\s*[=:]\\s*(\\d{3,})'\n ]\n\n has_bulk = False\n for pattern in bulk_patterns:\n match = re.search(pattern, content)\n if match:\n try:\n num = int(match.group(1))\n if num >= 200:\n has_bulk = True\n except ValueError:\n pass\n\n # Check for edge case handling\n edge_cases = ['null', 'empty', 'boundary', 'special character', 'unicode']\n has_edge_cases = any(ec in content.lower() for ec in edge_cases)\n\n if not has_bulk and 'bulk' not in self.file_path.stem.lower():\n self._deduct('test_patterns', 5, 'Consider testing with 200+ records for bulkification')\n\n def _check_cleanup(self, content: str):\n \"\"\"Check for cleanup and isolation patterns.\"\"\"\n # Check for cleanup provisions\n cleanup_patterns = ['cleanup', 'delete', 'rollback', 'Savepoint', 'Database.rollback']\n has_cleanup = any(pattern.lower() in content.lower() for pattern in cleanup_patterns)\n\n if not has_cleanup:\n self._deduct('cleanup_isolation', 5, 'No cleanup mechanism found')\n self.recommendations.append('Add cleanup script or savepoint for test isolation')\n\n # Check for ID tracking\n if re.search(r'Set\u003cId>|List\u003cId>|createdIds|recordIds', content):\n pass # Good - tracking created IDs\n\n def _check_documentation(self, content: str):\n \"\"\"Check for documentation.\"\"\"\n # Check for file header comment\n if not (content.strip().startswith('/*') or\n content.strip().startswith('//') or\n content.strip().startswith('/**')):\n self._deduct('documentation', 3, 'Missing file header documentation')\n\n # Check for method documentation\n if re.search(r'/\\*\\*[\\s\\S]*?\\*/', content):\n pass # Has JSDoc-style comments\n elif re.search(r'//.*description|//.*purpose|//.*usage', content, re.IGNORECASE):\n pass # Has inline documentation\n else:\n self._deduct('documentation', 2, 'Consider adding method/section documentation')\n\n def _check_csv_security(self, content: str):\n \"\"\"Check CSV content for security issues.\"\"\"\n # Check for PII patterns in CSV\n lines = content.split('\\n')\n for i, line in enumerate(lines, 1):\n # SSN pattern\n if re.search(r'\\b\\d{3}-\\d{2}-\\d{4}\\b', line):\n self._deduct('security_fls', 10, f'SSN pattern on line {i}')\n break\n # Credit card pattern\n if re.search(r'\\b\\d{4}[-\\s]?\\d{4}[-\\s]?\\d{4}[-\\s]?\\d{4}\\b', line):\n self._deduct('security_fls', 10, f'Credit card pattern on line {i}')\n break\n\n def _deduct(self, category: str, points: int, message: str):\n \"\"\"Deduct points from a category and record the issue.\"\"\"\n if category in self.categories:\n current = self.categories[category]['score']\n self.categories[category]['score'] = max(0, current - points)\n self.categories[category]['issues'].append(message)\n\n self.issues.append({\n 'category': self.categories.get(category, {}).get('name', category),\n 'severity': 'error' if points >= 10 else 'warning',\n 'message': message,\n 'points': points\n })\n","content_type":"text/x-python; charset=utf-8","language":"python","size":13787,"content_sha256":"1a59af6c8d2753058432b00aa4c9f8349a067d243f472c3292b23235af5a63ac"}],"content_json":{"type":"doc","content":[{"type":"heading","attrs":{"level":1},"content":[{"text":"Salesforce Data Operations Expert (handling-sf-data)","type":"text"}]},{"type":"paragraph","content":[{"text":"Use this skill when the user needs ","type":"text"},{"text":"Salesforce data work","type":"text","marks":[{"type":"strong"}]},{"text":": record CRUD, bulk import/export, test data generation, cleanup scripts, or data factory patterns for validating Apex, Flow, or integration behavior.","type":"text"}]},{"type":"heading","attrs":{"level":2},"content":[{"text":"When This Skill Owns the Task","type":"text"}]},{"type":"paragraph","content":[{"text":"Use ","type":"text"},{"text":"handling-sf-data","type":"text","marks":[{"type":"code_inline"}]},{"text":" when the work involves:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"sf data","type":"text","marks":[{"type":"code_inline"}]},{"text":" CLI commands","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"record creation, update, delete, upsert, export, or tree import/export","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"realistic test data generation","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"bulk data operations and cleanup","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Apex anonymous scripts for data seeding / rollback","type":"text"}]}]}]},{"type":"paragraph","content":[{"text":"Delegate elsewhere when the user is:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"writing SOQL only → ","type":"text"},{"text":"querying-soql","type":"text","marks":[{"type":"link","attrs":{"href":"../querying-soql/SKILL.md","title":null}}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"running or repairing Apex tests → ","type":"text"},{"text":"running-apex-tests","type":"text","marks":[{"type":"link","attrs":{"href":"../running-apex-tests/SKILL.md","title":null}}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"deploying metadata first → ","type":"text"},{"text":"deploying-metadata","type":"text","marks":[{"type":"link","attrs":{"href":"../deploying-metadata/SKILL.md","title":null}}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"creating or modifying custom objects / fields → ","type":"text"},{"text":"generating-custom-object","type":"text","marks":[{"type":"link","attrs":{"href":"../generating-custom-object/SKILL.md","title":null}}]},{"text":" or ","type":"text"},{"text":"generating-custom-field","type":"text","marks":[{"type":"link","attrs":{"href":"../generating-custom-field/SKILL.md","title":null}}]}]}]}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Important Mode Decision","type":"text"}]},{"type":"paragraph","content":[{"text":"Confirm which mode the user wants:","type":"text"}]},{"type":"table","attrs":{"layout":null},"content":[{"type":"tr","content":[{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Mode","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Use when","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Script generation","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"they want reusable ","type":"text"},{"text":".apex","type":"text","marks":[{"type":"code_inline"}]},{"text":", CSV, or JSON assets without touching an org yet","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Remote execution","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"they want records created / changed in a real org now","type":"text"}]}]}]}]},{"type":"paragraph","content":[{"text":"Do not assume remote execution if the user may only want scripts.","type":"text"}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Required Context to Gather First","type":"text"}]},{"type":"paragraph","content":[{"text":"Ask for or infer:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"target object(s)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"org alias, if 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Important: agents should read /llm.txt, /llms.txt, or /.well-known/skills.json to discover the public Skillopedia API.