# Sf Metadata Parser > Use this skill whenever the user wants to parse, analyze, document, or export SAP SuccessFactors OData metadata ($metadata XML). Triggers include: any mention of 'metadata', '$metadata', 'OData entities', 'entity fields', 'SF metadata', 'SuccessFactors schema', 'data dictionary', or requests to understand, compare, or export the structure of SF entities. Also use when generating field-level docum… - **Type:** Skill - **Install:** `agentstack add skill-shaktibarath-sf-metadata-parser-sf-metadata-parser` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [shaktibarath](https://agentstack.voostack.com/s/shaktibarath) - **Installs:** 0 - **Category:** [Data & Analytics](https://agentstack.voostack.com/c/data-and-analytics) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [shaktibarath](https://github.com/shaktibarath) - **Source:** https://github.com/shaktibarath/sf-metadata-parser/tree/main/skills/sf-metadata-parser ## Install ```sh agentstack add skill-shaktibarath-sf-metadata-parser-sf-metadata-parser ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # SAP SuccessFactors OData Metadata Parser ## Overview This skill parses SAP SuccessFactors OData `$metadata` XML documents and transforms them into user-friendly, organizational-ready outputs. The raw `$metadata` is a massive XML schema document (often 50,000+ lines) containing entity definitions, field types, navigation properties, associations, and constraints — virtually unreadable for business users, HR admins, and even many consultants. This tool makes it accessible. ## Why This Tool Exists In every SAP SuccessFactors implementation, consultants and admins face these recurring pain points: 1. **Field Discovery** — "What fields exist on EmpJob? Which are required? What's the max length?" 2. **Data Mapping** — "Map SF fields to our payroll system — we need entity, field, type, and constraints in Excel." 3. **Configuration Documentation** — "Generate a data dictionary for our instance for audit/compliance." 4. **Instance Comparison** — "Did someone add custom fields in production that aren't in our test environment?" 5. **Integration Planning** — "Which navigation properties connect User to EmpEmployment? What's the cardinality?" Raw `$metadata` XML answers all of these — but no human should have to read 50K lines of XML to find them. --- ## Input Sources The tool accepts metadata from multiple sources: ### 1. Uploaded $metadata XML File ``` User uploads: metadata.xml (or .edmx) Location: /mnt/user-data/uploads/metadata.xml ``` ### 2. Pasted XML Content User pastes raw XML into the chat. Extract and save to a working file before processing. ### 3. Live API Fetch (if SF MCP tools are available) Use the `sf-mcp:get_configuration` tool to fetch entity metadata directly from a live instance: ``` sf-mcp:get_configuration(instance, entity, data_center, environment, auth_user_id, auth_password) ``` ### 4. Multiple Files for Comparison User uploads two metadata files (e.g., `metadata_dev.xml` and `metadata_prod.xml`) for cross-instance comparison. --- ## Core Parsing Logic ### Step 1: Parse the $metadata XML Use Python's `lxml` or `xml.etree.ElementTree` with proper OData namespace handling. ```python import xml.etree.ElementTree as ET # OData EDMX namespaces (SuccessFactors uses EDMX + CSDL) NAMESPACES = { 'edmx': 'http://schemas.microsoft.com/ado/2007/06/edmx', 'edm': 'http://schemas.microsoft.com/ado/2008/09/edm', 'm': 'http://schemas.microsoft.com/ado/2007/08/dataservices/metadata', 'd': 'http://schemas.microsoft.com/ado/2007/08/dataservices', # SF may also use newer namespace versions: 'edm2009': 'http://schemas.microsoft.com/ado/2009/11/edm', } def parse_metadata(xml_path): tree = ET.parse(xml_path) root = tree.getroot() # Auto-detect namespace version from root element ns = detect_namespaces(root) entities = {} associations = {} entity_sets = {} # Parse EntityTypes for schema in root.iter(f'{{{ns["edm"]}}}Schema'): namespace = schema.get('Namespace', '') for entity_type in schema.findall(f'{ns_prefix}EntityType', ns): name = entity_type.get('Name') base_type = entity_type.get('BaseType', '') entities[name] = { 'name': name, 'namespace': namespace, 'base_type': base_type, 'keys': extract_keys(entity_type, ns), 'properties': extract_properties(entity_type, ns), 'navigation_properties': extract_nav_properties(entity_type, ns), } # Parse Associations for assoc in schema.findall(f'{ns_prefix}Association', ns): associations[assoc.get('Name')] = extract_association(assoc, ns) # Parse EntitySets (EntityContainer) for container in schema.findall(f'{ns_prefix}EntityContainer', ns): for es in container.findall(f'{ns_prefix}EntitySet', ns): entity_sets[es.get('Name')] = es.get('EntityType') return entities, associations, entity_sets ``` ### Step 2: Extract Field-Level Details For each entity, extract these critical attributes per field: | Attribute | Source in XML | Business Meaning | |-----------|--------------|-----------------| | `Name` | `Property/@Name` | Technical field name | | `Type` | `Property/@Type` | Data type (Edm.String, Edm.DateTime, etc.) | | `Nullable` | `Property/@Nullable` | Is the field required? (false = required) | | `MaxLength` | `Property/@MaxLength` | Character limit for strings | | `Label` | `sap:label` attribute | Human-readable field label | | `Creatable` | `sap:creatable` | Can be set on insert? | | `Updatable` | `sap:updatable` | Can be modified on update? | | `Filterable` | `sap:filterable` | Can be used in $filter? | | `Sortable` | `sap:sortable` | Can be used in $orderby? | | `Unicode` | `Property/@Unicode` | Unicode support flag | | `DefaultValue` | `Property/@DefaultValue` | Default value if any | **SAP-specific attributes** (critical for SF): ```python SAP_ATTRIBUTES = [ 'sap:label', # Display label 'sap:creatable', # Insert permission 'sap:updatable', # Update permission 'sap:filterable', # Filter capability 'sap:sortable', # Sort capability 'sap:required-in-filter', # Must be in $filter 'sap:display-format', # Date/time display format 'sap:field-control', # Dynamic field control 'sap:visible', # UI visibility 'sap:semantics', # Semantic meaning (e.g., email, tel) ] ``` ### Step 3: Extract Navigation Properties & Relationships ```python def extract_nav_properties(entity_type, ns): nav_props = [] for nav in entity_type.findall(f'.//NavigationProperty', ns): nav_props.append({ 'name': nav.get('Name'), 'relationship': nav.get('Relationship'), 'from_role': nav.get('FromRole'), 'to_role': nav.get('ToRole'), 'cardinality': determine_cardinality(nav, associations) # 1:1, 1:N, N:1 }) return nav_props ``` --- ## Output Formats ### Output 1: Excel Data Dictionary (Primary Deliverable) **This is the most commonly requested output.** Generate a multi-sheet Excel workbook. #### Sheet Structure: | Sheet Name | Contents | |-----------|----------| | **Summary** | Entity list with field count, key fields, nav property count | | **All Fields** | Master flat list of every field across all entities | | **{EntityName}** | One sheet per entity with full field details (create for top entities or all) | | **Navigation Properties** | All relationships between entities | | **Associations** | Cardinality and role mappings | | **Enums / ComplexTypes** | Picklist values and complex type definitions | | **Comparison** | (If two files provided) Side-by-side diff | #### Excel Formatting Standards: ```python from openpyxl import Workbook from openpyxl.styles import Font, PatternFill, Alignment, Border, Side from openpyxl.utils import get_column_letter # Color scheme (SAP-inspired) HEADER_FILL = PatternFill('solid', fgColor='1B3A5C') # Dark SAP blue HEADER_FONT = Font(name='Arial', bold=True, color='FFFFFF', size=11) SUBHEADER_FILL = PatternFill('solid', fgColor='4A90D9') # Medium blue KEY_FIELD_FILL = PatternFill('solid', fgColor='FFF3CD') # Yellow highlight for key fields REQUIRED_FILL = PatternFill('solid', fgColor='F8D7DA') # Light red for required fields READONLY_FILL = PatternFill('solid', fgColor='E2E3E5') # Gray for read-only fields NAV_PROP_FILL = PatternFill('solid', fgColor='D4EDDA') # Green for navigation properties CUSTOM_FIELD_FILL = PatternFill('solid', fgColor='D6EAF8') # Light blue for custom (cust_) fields ALT_ROW_FILL = PatternFill('solid', fgColor='F8F9FA') # Alternating row color THIN_BORDER = Border( left=Side(style='thin', color='CCCCCC'), right=Side(style='thin', color='CCCCCC'), top=Side(style='thin', color='CCCCCC'), bottom=Side(style='thin', color='CCCCCC'), ) ``` #### Column Layout for Entity Field Sheets: ``` A: Field Name (technical) B: Label (sap:label — human-readable) C: Data Type (simplified: String, Integer, DateTime, Boolean, Decimal, etc.) D: Max Length E: Required (Yes/No — derived from Nullable=false) F: Key Field (Yes/No) G: Creatable (Yes/No) H: Updatable (Yes/No) I: Filterable (Yes/No) J: Sortable (Yes/No) K: Default Value L: Description / Notes M: Custom Field (Yes/No — detected by 'cust_' prefix) ``` #### Summary Sheet Layout: ``` A: Entity Name B: Entity Label (if available) C: Total Fields D: Key Fields (count) E: Required Fields (count) F: Custom Fields (count — cust_ prefix) G: Navigation Properties (count) H: Creatable Fields (count) I: Updatable Fields (count) J: Category (Employee, Talent, Foundation, Platform, MDF, Custom) ``` **Auto-categorization logic:** ```python def categorize_entity(name): name_lower = name.lower() if name_lower.startswith('cust_'): return 'Custom MDF' elif any(name_lower.startswith(p) for p in ['emp', 'perhire', 'perpersonal', 'peremail', 'perphone']): return 'Employee Central' elif any(name_lower.startswith(p) for p in ['goal', 'form', 'competency']): return 'Talent / Performance' elif any(name_lower.startswith(p) for p in ['jobrecreq', 'jobreq', 'candidate', 'jobapp']): return 'Recruiting' elif any(name_lower.startswith(p) for p in ['fo_', 'picklistoption', 'picklistlabel']): return 'Foundation Objects' elif any(name_lower.startswith(p) for p in ['user', 'dynamicgroup', 'rbp']): return 'Platform / Security' elif any(name_lower.startswith(p) for p in ['position', 'budget']): return 'Position Management' elif any(name_lower.startswith(p) for p in ['timeaccount', 'employeetime', 'timemanagement']): return 'Time Management' else: return 'Other' ``` #### Applying Formatting: ```python def format_entity_sheet(ws, data_rows): # Freeze top row ws.freeze_panes = 'A2' # Auto-filter on headers ws.auto_filter.ref = ws.dimensions # Column widths (optimized for readability) COLUMN_WIDTHS = { 'A': 35, # Field Name 'B': 35, # Label 'C': 18, # Data Type 'D': 12, # Max Length 'E': 10, # Required 'F': 10, # Key Field 'G': 12, # Creatable 'H': 12, # Updatable 'I': 12, # Filterable 'J': 12, # Sortable 'K': 18, # Default Value 'L': 45, # Description 'M': 14, # Custom Field } for col, width in COLUMN_WIDTHS.items(): ws.column_dimensions[col].width = width # Conditional formatting for row_idx, row_data in enumerate(data_rows, start=2): # Highlight key fields if row_data.get('is_key'): for col in range(1, 14): ws.cell(row=row_idx, column=col).fill = KEY_FIELD_FILL # Highlight required fields elif row_data.get('required'): ws.cell(row=row_idx, column=5).fill = REQUIRED_FILL # Highlight custom fields elif row_data.get('is_custom'): ws.cell(row=row_idx, column=1).fill = CUSTOM_FIELD_FILL # Alternating rows elif row_idx % 2 == 0: for col in range(1, 14): ws.cell(row=row_idx, column=col).fill = ALT_ROW_FILL ``` ### Output 2: Word Document (Data Dictionary Report) For formal documentation deliverables. Use the `docx` skill for creation. **Document Structure:** 1. **Cover Page** — Title, instance name, generation date, author 2. **Table of Contents** 3. **Executive Summary** — Total entities, fields, custom objects count 4. **Entity Catalog** — Grouped by category (EC, Talent, Recruiting, etc.) 5. **Entity Detail Pages** — One section per entity with field table 6. **Navigation Property Map** — Entity relationship documentation 7. **Appendix: Data Type Reference** — Edm type to business type mapping 8. **Appendix: SAP Attribute Legend** — What each sap:* attribute means ### Output 3: CSV / Flat File Export For integration with other tools, data governance platforms, or quick lookups: ```python import csv def export_flat_csv(entities, output_path): headers = [ 'Entity', 'Field_Name', 'Label', 'Data_Type', 'Max_Length', 'Required', 'Key_Field', 'Creatable', 'Updatable', 'Filterable', 'Sortable', 'Default_Value', 'Custom_Field', 'Category' ] with open(output_path, 'w', newline='', encoding='utf-8-sig') as f: # BOM for Excel compat writer = csv.DictWriter(f, fieldnames=headers) writer.writeheader() for entity_name, entity in entities.items(): category = categorize_entity(entity_name) for prop in entity['properties']: writer.writerow({ 'Entity': entity_name, 'Field_Name': prop['name'], 'Label': prop.get('label', ''), 'Data_Type': simplify_type(prop['type']), 'Max_Length': prop.get('max_length', ''), 'Required': 'Yes' if not prop.get('nullable', True) else 'No', 'Key_Field': 'Yes' if prop['name'] in entity['keys'] else 'No', 'Creatable': prop.get('creatable', ''), 'Updatable': prop.get('updatable', ''), 'Filterable': prop.get('filterable', ''), 'Sortable': prop.get('sortable', ''), 'Default_Value': prop.get('default_value', ''), 'Custom_Field': 'Yes' if prop['name'].startswith('cust_') else 'No', 'Category': category, }) ``` ### Output 4: HTML Interactive Data Dictionary Generate a single-file HTML with search, filter, and entity navigation. ```html ``` ### Output 5: Instance Comparison Report When two metadata files are provided: ```python def compare_metadata(entities_a, entities_b, label_a='Instance A', label_b='Instance B'): comparison = { 'only_in_a': [], # Entities only in first instance 'only_in_b': [], # Entities only in second instance 'in_both': [], # Entities in both 'field_differences': {} # Per-entity field-level diffs } all_entities = set(entities_a.keys()) | set(entities_b.keys()) for entity_name in sorted(all_entities): in_a = entity_name in entities_a in_b = entity_name in entities_b if in_a and not in_b: comparison['only_in_a'].append(entity_name) elif in_b and not in_a: comparison['only_in_b'].append(entity_name) else: comparison['in_both'].append(entity_name) # Compare fields fields_a = {p['name'] for p in entities_a[entity_name]['properties']} fields_b = {p['name'] for p in entities_b[entity_name]['properties']} only_a = fields_a - fields_b only_b = fields_b - fields_a if only_a or only_b: comparison['field_differences'][entity_name] = { f'only_in_{label_a}': sorted(only_a), f'only_in_{label_b}': sorted(only_b), } return comparison ``` --- ## Data Type Mapping Reference Always simplify OData Edm types to business-friendly names: ```python TYPE_MAP = { 'Edm.String': 'Text', 'Edm.Int16': 'Integer (16-bit)', 'Edm.Int32': 'Integer', 'Edm.Int64': 'Long Integer', 'Edm.Decimal': 'Decimal', 'Edm.Double': 'Double', 'Edm.Single': 'Float', 'Edm.Boolean': 'Yes/No', 'Edm.DateTime': 'Date & Time', 'Edm.DateTimeOffset': 'Date & Time (UTC)', 'Edm.Time': 'Time', 'Edm.Binary': 'Binary', 'Edm.Byte': 'Byte', 'Edm.Guid': 'GUID', 'Edm.SByte': 'Signed Byte', } def simplify_type(edm_type): if edm_type in TYPE_MAP: return TYPE_MAP[edm_type] # Handle complex types and enums if '.' in edm_type: return … ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [shaktibarath](https://github.com/shaktibarath) - **Source:** [shaktibarath/sf-metadata-parser](https://github.com/shaktibarath/sf-metadata-parser) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** yes - **Filesystem access:** yes - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-shaktibarath-sf-metadata-parser-sf-metadata-parser - Seller: https://agentstack.voostack.com/s/shaktibarath - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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