القائمة
Unified management of episodic, semantic, procedural, and relational memory within the factory workspace.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Automated governance, hook installation, pre-commit validation, branch isolation, and safe commit operations.
Enforcement of safety guardrails, axiom verification, secret scanning, and mutability protections.
Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers.
Integration of agent systems with blockchain protocols, contracts, event stores, reputation networks, and collective verification engines.
AI model configuration, LLM memoization, agentic RAG search, and vector library maintenance.
Catalog generation, reference link verification, workshop documentation building, and knowledge gap analysis.
| 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