Entity and fact extraction for user profiling and personalization
--- name: entity-memory-extraction description: Entity and fact extraction for user profiling and personalization allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:natural-language-processing, skill-area:context-management] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:feature-development, workflow:ml-model-lifecycle] --- # Entity Memory Extraction Skill ## Capabilities - Extract entities from conversations - Build and update user profiles - Track preferences and facts - Implement entity disambiguation - Design entity relationship graphs - Configure extraction rules and schemas ## Target Processes - long-term-memory-management - conversational-persona-design ## Implementation Details ### Extraction Types 1. **Named Entities**: People, places, organizations 2. **User Preferences**: Likes, dislikes, interests 3. **Facts**: Stated information about user 4. **Temporal**: Dates, events, schedules 5. **Relationships**: Connections between entities ### Configuration Options - Extraction model selection - Entity schema definition - Confidence thresholds - Update policies - Storage backend ### Best Practices - Define clear entity schemas - Handle entity conflicts - Implement confidence scoring - Regular profile validation - Privacy considerations ### Dependencies - langchain - spacy (optional) - Custom extraction models--- name: entity-memory-extraction description: Entity and fact extraction for user profiling and personalization allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:natural-language-processing, skill-area:context-management] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:feature-development, workflow:ml-model-lifecycle] --- # Entity Memory Extraction Skill ## Capabilities - Extract entities from conversations - Build and update user profiles - Track preferences and facts - Implement entity disambiguation - Design entity relationship graphs - Configure extraction rules and schemas ## Target Processes - long-term-memory-management - conversational-persona-design ## Implementation Details ### Extraction Types 1. **Named Entities**: People, places, organizations 2. **User Preferences**: Likes, dislikes, interests 3. **Facts**: Stated information about user 4. **Temporal**: Dates, events, schedules 5. **Relationships**: Connections between entities ### Configuration Options - Extraction model selection - Entity schema definition - Confidence thresholds - Update policies - Storage backend ### Best Practices - Define clear entity schemas - Handle entity conflicts - Implement confidence scoring - Regular profile validation - Privacy considerations ### Dependencies - langchain - spacy (optional) - Custom extraction models
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.