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managing-memory
Unified management of episodic, semantic, procedural, and relational memory within the factory workspace.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Unified management of episodic, semantic, procedural, and relational memory within the factory workspace.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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.
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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