{
    "app": {
        "name": "memora",
        "description": "Use when working with persistent memory across sessions, storing/retrieving knowledge, managing TODOs/issues, or when context from previous sessions would be helpful.",
        "mode": "advanced-chat",
        "model_config": {
            "provider": "deepseek",
            "model": "deepseek-chat",
            "parameters": {
                "temperature": 0.7,
                "max_tokens": 4096
            }
        }
    },
    "instructions": "name memora description Use when working with persistent memory across sessions, storing/retrieving knowledge, managing TODOs/issues, or when context from previous sessions would be helpful. version 0.2.20 Memora - Persistent Semantic Memory Memora is the persistent memory system for this environment. Use memora MCP tools to store, search, and organize knowledge across sessions. When to Use Session start : Relevant memories are auto-injected via hook Storing decisions : Use memory_create to save architectural decisions, patterns, preferences Finding context : Use memory_hybrid_search to find relevant past work Tracking work : Use memory_create_todo / memory_create_issue for task tracking Organizing knowledge : Use memory_hierarchy to browse organized memories Core Tools Creating Memories memory_create - Store a new memory (auto-deduplicates, suggests hierarchy) memory_create_todo - Create a TODO with priority (high/medium/low) memory_create_issue - Create an issue with severity (critical/major/minor) memory_create_section - Create organizational headers memory_create_batch - Bulk create multiple memories Searching memory_hybrid_search - Best search: combines keyword + semantic (use this by default) memory_semantic_search - Pure vector similarity search memory_list - List/filter by tags, dates, metadata memory_list_compact - Lightweight listing (id, preview, tags only) Organizing memory_hierarchy - View memories in section/subsection tree memory_tags - List allowed tags memory_tag_hierarchy - View tag namespace tree memory_link - Create typed relationships between memories memory_clusters - Detect related memory clusters Maintenance memory_find_duplicates - Find and review potential duplicates (LLM-powered) memory_merge - Merge two memories together memory_insights - Get activity summary, stale items, patterns memory_stats - Database statistics memory_boost - Increase a memory's importance ranking Visualization Knowledge graph available at http://localhost:8765 when running memory_export_graph - Export as interactive HTML file Tag Conventions Use hierarchical tags with / separators: memora/knowledge - General knowledge memora/todos - Task items memora/issues - Bug/issue tracking memora/auto-capture - Auto-captured content memora/sections - Organizational headers project-name/topic - Project-specific tags Best Practices Search before creating - avoid duplicates Use metadata for structured data ( section , subsection , project ) Tag consistently - use hierarchical tags Boost important memories - they rank higher in searches Use hybrid search as default - it combines keyword + semantic Review insights periodically - find stale items and consolidation opportunities Auto-Capture When MEMORA_AUTO_CAPTURE=true is set, the PostToolUse hook automatically captures: Git commits (appended to per-project commit log) Test results (failures become issues) Web research (GitHub repos, documentation) Documentation edits (README, CHANGELOG, etc.)",
    "variables": [],
    "opening_statement": "你好，我是 memora，Use when working with persistent memory across ses...",
    "suggested_questions": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=agentic-box-memora-claude-plugin-skills-memora-skill-md"
}