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Unified management of episodic, semantic, procedural, and relational memory within the factory workspace.
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Based on SOC occupation classification
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| name | managing-memory |
| description | Unified management of episodic, semantic, procedural, and relational memory within the factory workspace. |
| type | skill |
| version | 1.0.0 |
| category | routing |
| agents | ["python-ai-specialist","master-system-orchestrator"] |
| knowledge | ["memory-integration.json"] |
| scripts | ["scripts/memory/check_memory.py","scripts/memory/clean_memory.py","scripts/memory/embedding_service.py","scripts/memory/entity_indexer.py","scripts/memory/entity_store.py","scripts/memory/episodic_logger.py","scripts/memory/experience_collector.py","scripts/memory/governance_gates.py","scripts/memory/hook_session_end.py","scripts/memory/hook_session_start.py","scripts/memory/induction_engine.py","scripts/memory/init_collections.py","scripts/memory/learn_memory_security.py","scripts/memory/mcp_sync_bridge.py","scripts/memory/memory_approver.py","scripts/memory/memory_cleanup.py","scripts/memory/memory_cli.py","scripts/memory/memory_config.py","scripts/memory/memory_database.py","scripts/memory/memory_integration.py","scripts/memory/memory_store.py","scripts/memory/procedural_indexer.py","scripts/memory/profile_rag_startup.py","scripts/memory/reflection_engine.py","scripts/memory/semantic_indexer.py","scripts/memory/store_lessons_learned.py"] |
| tools | ["mcp_memory_read_graph","mcp_memory_open_nodes","mcp_memory_search_nodes","mcp_qdrant-rag_search_memory_entity"] |
| related_skills | ["managing-knowledge-graphs","managing-memory-bank"] |
| references | [".agent/knowledge/core/manifest.json"] |
| settings | {"auto_approve":false,"timeout_seconds":300} |
This skill covers the tools, scripts, and processes used to synchronize, index, clean, and reflect upon episodic, semantic, procedural, and relational memories across the workspace and vector/graph databases.
Use this skill when performing memory maintenance, indexing new entities, reflecting on logs, running experience collectors, or checking memory health.
cursor-factory python interpreter.Follow these procedures to manage the workspace memory systems.
To verify memory server availability and collections:
conda run -p D:\Anaconda\envs\cursor-factory python scripts/memory/check_memory.py
conda run -p D:\Anaconda\envs\cursor-factory python scripts/memory/init_collections.py
To log sessions and invoke the reflection engine:
conda run -p D:\Anaconda\envs\cursor-factory python scripts/memory/hook_session_start.py
conda run -p D:\Anaconda\envs\cursor-factory python scripts/memory/reflection_engine.py