# Send Overkill Memory System to your agent Use the source page and any available docs to guide the install because the item is currently unstable or timing out. ## Fast path - Open the source page via Review source status. - If you can obtain the package, extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the source page and extracted files. ## Suggested prompts ### New install ```text I tried to install a skill package from Yavira, but the item is currently unstable or timing out. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required. ``` ### Upgrade existing ```text I tried to upgrade a skill package from Yavira, but the item is currently unstable or timing out. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "overkill-memory-system", "name": "Overkill Memory System", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/Broedkrummen/overkill-memory-system", "canonicalUrl": "https://clawhub.ai/Broedkrummen/overkill-memory-system", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/overkill-memory-system", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=overkill-memory-system", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "BRAIN_INTEGRATION.md", "FILE_SEARCH_INTEGRATION.md", "FINAL_ARCHITECTURE.md", "KG_INTEGRATION.md", "MULTI_AGENT_CHROMA.md", "NEURAL_MEMORY_ANALYSIS.md" ], "downloadMode": "manual_only", "sourceHealth": { "source": "tencent", "slug": "overkill-memory-system", "status": "unstable", "reason": "timeout", "recommendedAction": "retry_later", "checkedAt": "2026-05-06T19:23:29.241Z", "expiresAt": "2026-05-07T07:23:29.241Z", "httpStatus": null, "finalUrl": null, "contentType": null, "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=overkill-memory-system", "error": "Timed out after 5000ms", "slug": "overkill-memory-system" }, "scope": "item", "summary": "Item is unstable.", "detail": "This item is timing out or returning errors right now. Review the source page and try again later.", "primaryActionLabel": "Review source status", "primaryActionHref": "https://clawhub.ai/Broedkrummen/overkill-memory-system" }, "validation": { "installChecklist": [ "Wait for the source to recover or retry later.", "Review SKILL.md only after the download returns a real package.", "Treat this source as transient until the upstream errors clear." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/overkill-memory-system", "downloadUrl": "https://openagent3.xyz/downloads/overkill-memory-system", "agentUrl": "https://openagent3.xyz/skills/overkill-memory-system/agent", "manifestUrl": "https://openagent3.xyz/skills/overkill-memory-system/agent.json", "briefUrl": "https://openagent3.xyz/skills/overkill-memory-system/agent.md" } } ``` ## Documentation ### VERSION 1.9.3 (SPEED-FIRST) A comprehensive 6-tier memory architecture with neuroscience integration, WAL protocol, and full automation for OpenClaw agents. ### Overview The Ultimate Unified Memory System implements a biologically-inspired, speed-first memory hierarchy. It provides persistent, contextual memory across agent sessions with automatic importance weighting, emotional tagging, and value-based retention. ### What It Does Brain-Full Architecture: 6 brain regions (Hippocampus, Amygdala, VTA, Basal Ganglia, Insula, ACC) Speed-First Architecture: Optimized for ~5ms average query time Fast File Search: Uses fd + rg for 10x faster file tier searching Knowledge Graph: Structured atomic facts with versioning Self-Improving: Continuous learning from errors and corrections Self-Reflection: Periodic self-assessment and performance review Multi-Agent Support: Shared + private ChromaDB areas per agent 6-Tier Memory Architecture: From instant recall (HOT) to archival (COLD/GIT-NOTES) Hybrid Neuroscience: Filter + Ranker approach for precision + speed WAL (Write-Ahead Log) Protocol: Ensures no memory is ever lost Neuroscience Integration: Hippocampus (importance), Amygdala (emotions), VTA (rewards/motivation) Error Learning: Tracks and learns from user corrections Spaced Repetition: FSRS-6 via Vestige for natural memory decay Semantic Search: ChromaDB-powered vector storage for contextual retrieval Cloud Backup: Supermemory integration for cross-device backup (NOT in query path) Full Automation: Cron jobs for cross-session messages, platform posts, diary entries, and proactive memory maintenance ### Speed Targets ScenarioTimeCompiled query match~0msUltra-hot hit~0.1msHot cache hit~1msMem0 hit~22msFull search~55msAverage~5ms Note: Supermemory is NOT in the query path - it's a background sync only (daily backup). This keeps queries fast (~5ms). Cloud access is only for backup/restore, not real-time queries. ### Speed-First Architecture Diagram ┌─────────────────────────────────────────────────────────────────┐ │ USER QUERY │ └─────────────────────────┬───────────────────────────────────────┘ │ ┌───────────────▼───────────────┐ │ ULTRA-HOT (Dict) │ │ Last 10 queries ~0.1ms │ │ (RETURN if hit!) │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ HOT CACHE (Redis) │ │ Recent queries ~1ms │ │ (RETURN if hit!) │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ COMPILED QUERIES │ │ Pre-parsed common queries │ │ ~0ms (dict lookup) │ │ (USE if match!) │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ EMOTIONAL DETECTOR │ │ preference/error/important │ │ ~0.5ms │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ BLOOM FILTER │ │ "Does it exist?" ~0ms │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ MEM0 (FIRST!) │ │ Fast cache ~20ms │ │ 80% token savings │ │ (RETURN if hit!) │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ EARLY WEIGHTING │ │ Adjust tier weights │ │ ~1ms │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ RUN TIERS PARALLEL │ │ acc-err, vestige, chromadb, │ │ gitnotes, file │ │ ~30ms │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ MERGE + RANKING │ │ Neuroscience scoring │ │ PASS 1: Quick filter │ │ PASS 2: Full rank │ │ ~10ms │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ CONFIDENCE EARLY EXIT │ │ confidence > 0.95? return 1│ │ gap > 0.5? return 1 │ └───────────────┬───────────────┘ │ ┌───────────────▼───────────────┐ │ BACKGROUND SYNC │ │ Supermemory (daily backup) │ │ NOT in query path! │ └───────────────┬───────────────┘ │ ▼ ┌───────────────┐ │ RESULTS │ │ (~5-15ms) │ └───────────────┘ ### 1. Speed Optimizations (NEW in v1.3.0) OptimizationTime SavedUltra-Hot TierIn-memory dict for last 10 queries (~0.1ms)Compiled QueriesPre-parsed common queries (~0ms)Lazy LoadingImport heavy libs only when neededConfidence Early ExitSkip ranking if confident enoughMem0 First80% queries hit here (~22ms)Parallel TiersAll tiers queried simultaneously ### 2. Six-Tier Memory Architecture TierNameStorageRetentionUse Case1HOTSession stateCurrent sessionActive context, WAL buffer2WARMDaily notes24-48 hoursRecent conversations, working memory3TEMPCacheMinutes-hoursTemporary processing, scratchpad4COLDCore memoryWeeks-monthsImportant facts, decisions, preferences5ARCHIVEDiaryMonths-yearsLong-term journal, milestone memories6COLD-STORAGEGit-NotesIndefinitePermanent knowledge base ### 2. Neuroscience Components Hippocampus (Importance Scoring) Analyzes content for importance signals Maintains index.json with memory importance scores Auto-weights memories based on repetition and context Amygdala (Emotional Tagging) Detects 8 emotions: joy, sadness, anger, fear, curiosity, connection, accomplishment, fatigue Tracks emotional dimensions: valence, arousal, connection, curiosity, energy Stores state in emotional-state.json VTA (Value/Reward System) Computes motivation scores based on reward types Reward categories: accomplishment, social, curiosity, connection, creative, competence Drives attention toward high-value memories ### 3. Hybrid Search (NEW in v1.3.0) Emotional Detector Detects query intent: preference, error, important, recent, project, general Adjusts tier weights based on detected intent Runs AFTER cache checks (only when needed) Early Weighting Query TypeKeywordsWeight AdjustmentsError/Fix"bug", "fix", "error"acc-error: 2xPreference"prefer", "like", "always"vestige: 2xImportant"remember", "critical"all: 1.5xRecent"yesterday", "last week"hot: 2xProject"project", "architecture"gitnotes: 1.5x ### 4. Hybrid Neuroscience (NEW in v1.3.0) Two-pass approach for precision + speed: PassWhatWhenPass 1Quick filter (skip 0 importance)High-importance queriesPass 2Full ranking (all components)Always Scoring Formula Final Score = (Base Relevance × 0.25) + (Importance × 0.30) + ← Hippocampus (Value × 0.25) + ← VTA (Emotion Match × 0.20) ← Amygdala ### 5. Error Learning (NEW in v1.3.0) acc-error-memory integration Tracks error patterns over time Records user corrections Learns from mistakes High priority in search results ### 6. Spaced Repetition (NEW in v1.3.0) vestige integration (FSRS-6) Memories fade naturally like human memory Preferences strengthen with use Solutions decay if unused ### 7. Write-Ahead Log (WAL) Protocol Session state maintained in SESSION-STATE.md WAL buffer ensures atomic commits Crash recovery from uncommitted state ### 4. Automation Features Cron Inbox: Cross-session messages via cron-inbox.md Platform Posts: Tracks Discord/Telegram posts in platform-posts.md Diary Entry: Daily journal entries in diary/ directory Daily Notes: Session logs in daily/ directory Heartbeat State: Tracks periodic check timestamps ### Prerequisites # Ensure Python 3.8+ is available python3 --version # Optional: ChromaDB for semantic search pip install chromadb # Optional: Ollama for embeddings # Install from https://github.com/ollama/ollama ### Step 1: Install the Skill # The skill should be placed in your skills directory # ~/.openclaw/workspace/skills/overkill-memory-system/ ### Step 2: Configure Environment Copy .env.example to .env and configure: cp .env.example .env # Edit .env with your preferences ### Step 3: Initialize Memory System python3 cli.py init This creates all required memory files: ~/.openclaw/memory/SESSION-STATE.md ~/.openclaw/memory/MEMORY.md ~/.openclaw/memory/cron-inbox.md ~/.openclaw/memory/platform-posts.md ~/.openclaw/memory/strategy-notes.md ~/.openclaw/memory/heartbeat-state.json ~/.openclaw/memory/diary/ ~/.openclaw/memory/daily/ ~/.openclaw/memory/chroma/ ~/.openclaw/memory/git-notes/ ### Initialization # Initialize memory system files python3 cli.py init # Initialize with custom memory base path python3 cli.py init --path /custom/path ### Memory Operations # Add a memory with auto-detected importance & emotions python3 cli.py add "Finished the project, feeling accomplished!" # Add memory with explicit importance (0.0-1.0) python3 cli.py add "Important decision made" --importance 0.9 # Add with explicit emotions python3 cli.py add "Excited about the new feature" --emotions joy,curiosity # Add with reward/value tracking python3 cli.py add "Shipped v2.0" --reward accomplishment --intensity 0.8 ### Retrieval # Search memories (hybrid - default, uses all optimizations) python3 cli.py search "project updates" # Fast mode (cache + ultra-hot only) python3 cli.py search "query" --fast # Full search (all tiers) python3 cli.py search "query" --full # Get recent memories python3 cli.py recent --limit 10 # Get memories by importance threshold python3 cli.py important --threshold 0.7 ### Error Tracking (NEW) # Track an error python3 cli.py error track "Forgot to add import" # Show error patterns python3 cli.py error patterns # Show corrections made python3 cli.py error corrections # Error statistics python3 cli.py error stats ### Vestige Integration (NEW) # Search vestige memories python3 cli.py vestige search "user preferences" # Ingest with tags python3 cli.py vestige ingest "User prefers dark mode" --tags preference # Promote memory (strengthen) python3 cli.py vestige promote # Demote memory (weaken) python3 cli.py vestige demote # Check vestige stats python3 cli.py vestige stats ### File Search (NEW) # Search by file name (uses fd) python3 cli.py file search "*.md" # Search by content (uses rg) python3 cli.py file content "TODO" # Fast combined search python3 cli.py file fast "pattern" ### Knowledge Graph (NEW) # Add atomic fact python3 cli.py kg add --entity "people/kasper" --category "preference" --fact "Prefers TypeScript" # Supersede old fact python3 cli.py kg supersede --entity "people/kasper" --old kasper-001 --fact "New fact" # Generate entity summary python3 cli.py kg summarize --entity "people/kasper" # Search knowledge graph python3 cli.py kg search "preference" # List all entities python3 cli.py kg list ### Self-Improving (NEW) # Log an error python3 cli.py improve error "Command failed" --context "details" # Log user correction python3 cli.py improve correct "No, that's wrong" --context "user corrected me" # Log feature request python3 cli.py improve request "Need markdown support" # Log best practice python3 cli.py improve better "Use async for I/O" --context "found during work" # Get all learnings python3 cli.py improve list ### Neuroscience (NEW) # Show neuroscience statistics python3 cli.py neuro stats # Analyze text for neuroscience scores python3 cli.py neuro analyze "I'm excited about this project!" ### Session Management # Start new session (flushes WAL to daily) python3 cli.py session new # End session (commits WAL buffer) python3 cli.py session end # Show session state python3 cli.py session status ### Neuroscience Queries # Get current emotional state python3 cli.py brain state # Get motivation/drive level python3 cli.py brain drive # Update emotional dimensions python3 cli.py brain update --valence 0.8 --arousal 0.6 ### Daily & Diary # Create daily note entry python3 cli.py daily "What happened today" # Create diary entry (prompts for date) python3 cli.py diary "Reflecting on the week" # List recent diary entries python3 cli.py diary list --limit 5 ### Automation # Process cron inbox messages python3 cli.py cron process # Sync platform posts python3 cli.py sync posts # Run memory analysis python3 cli.py analyze ### Utilities # Show memory statistics python3 cli.py stats # Export memory backup python3 cli.py export /path/to/backup/ # Import memory backup python3 cli.py import /path/to/backup/ ### Configuration (.env) # Memory base directory MEMORY_BASE=/home/user/.openclaw/memory # ChromaDB settings (optional) CHROMA_URL=http://localhost:8100 CHROMA_COLLECTION=memory-v2 # Ollama settings (optional) OLLAMA_URL=http://localhost:11434 EMBEDDING_MODEL=bge-m3 # Capture settings POLL_INTERVAL=300 # Processing settings CHUNK_SIZE=512 CHUNK_OVERLAP=50 # Retrieval settings CACHE_TTL=3600 MAX_RESULTS=10 ### Tier 1: HOT (Session State) Location: ~/.openclaw/memory/SESSION-STATE.md Size: Keep under 50KB Content: Active context, current task, recent messages ### Tier 2: WARM (Daily) Location: ~/.openclaw/memory/daily/YYYY-MM-DD.md Size: Up to 100KB per day Content: Daily logs, conversation summaries ### Tier 3: TEMP (Cache) Location: ~/.cache/memory-v2/ Size: Auto-cleaned after 24h Content: Processing scratchpad, temporary embeddings ### Tier 4: COLD (Core) Location: ~/.openclaw/memory/MEMORY.md Size: Keep under 500KB Content: Key facts, decisions, preferences, lessons learned ### Tier 5: ARCHIVE (Diary) Location: ~/.openclaw/memory/diary/ Size: Unlimited Content: Personal journal, milestone reflections ### Tier 6: COLD-STORAGE (Git-Notes) Location: ~/.openclaw/memory/git-notes/ Size: Unlimited Content: Knowledge base, permanent reference ### Recommended Cron Setup # Process cron inbox every 5 minutes */5 * * * * cd ~/.openclaw/workspace-cody/skills/overkill-memory-system && python3 cli.py cron process >> /var/log/memory-cron.log 2>&1 # Sync platform posts every 15 minutes */15 * * * * cd ~/.openclaw/workspace-cody/skills/overkill-memory-system && python3 cli.py sync posts >> /var/log/memory-sync.log 2>&1 # Daily diary entry at 9 PM 0 21 * * * cd ~/.openclaw/workspace-cody/skills/overkill-memory-system && python3 cli.py diary "Daily reflection" >> /var/log/memory-diary.log 2>&1 # Weekly memory analysis (Sunday 10 PM) 0 22 * * 0 cd ~/.openclaw/workspace-cody/skills/overkill-memory-system && python3 cli.py analyze >> /var/log/memory-analyze.log 2>&1 ### Heartbeat Integration Add to HEARTBEAT.md: ## Memory System Checks - [ ] Check cron-inbox for cross-session messages - [ ] Check platform-posts for new activity - [ ] Review recent daily notes for important context - [ ] Update emotional state if significantly changed ### Memory System Won't Initialize # Check directory permissions ls -la ~/.openclaw/memory/ # Manually create directory mkdir -p ~/.openclaw/memory ### ChromaDB Connection Failed # Check if ChromaDB is running curl http://localhost:8100/api/v1/heartbeat # Or use keyword search fallback python3 cli.py search "query" --method keyword ### Ollama Embeddings Not Working # Check Ollama is running curl http://localhost:11434/api/tags # Verify embedding model ollama list ### Session State Not Persisting # Manually flush WAL buffer python3 cli.py session end # Check session file cat ~/.openclaw/memory/SESSION-STATE.md ### Memory Search Returns No Results # Rebuild search index python3 cli.py analyze # Try keyword fallback python3 cli.py search "term" --method keyword ### Git-Notes Sync Issues # Check git-notes directory ls -la ~/.openclaw/memory/git-notes/ # Initialize git repo if needed cd ~/.openclaw/memory/git-notes && git init ### File Structure overkill-memory-system/ ├── SKILL.md # This file ├── README.md # Quick start guide ├── .env.example # Environment template ├── cli.py # Main CLI interface ├── config.py # Configuration ├── scripts/ │ └── analyze_memories.py # Memory analysis tool ├── templates/ # Future: custom templates └── ULTIMATE_UNIFIED_FRAMEWORK.md # Full framework docs ### Credits & Sources vestige - FSRS-6 spaced repetition for natural memory decay and preferences acc-error-memory - Error pattern tracking and correction learning Built with neuroscience-inspired architecture: Hippocampus: Importance-based memory consolidation Amygdala: Emotional tagging and valence processing VTA: Reward-driven attention and motivation Based on the Ultimate Unified Memory Framework (ULTIMATE_UNIFIED_FRAMEWORK.md) ### Credits & Sources vestige - FSRS-6 spaced repetition for natural memory decay and preferences acc-error-memory - Error pattern tracking and correction learning This skill was built by integrating ideas and features from the following ClawHub skills: ### Core Architecture elite-longterm-memory - WAL Protocol, Git-Notes knowledge graph, SESSION-STATE.md concept jarvis-memory-architecture - Cron inbox, diary, daily logs, platform post tracking, adaptive learning memory-hygiene - Auto-cleanup, storage guidelines ### Neuroscience Components hippocampus-memory - Importance-weighted recall and memory encoding amygdala-memory - Emotional tagging and processing vta-memory - Value scoring and motivation tracking ### Storage & Integration chromadb-memory - Vector storage integration (ChromaDB + Ollama bge-m3) supermemory-free - Optional cloud backup integration mem0 - Auto-fact extraction (80% token reduction) memory-system-v2 - Core unified memory framework ### Created By Initial implementation by Cody (AI coding specialist) Framework designed by Broedkrummen Built with OpenClaw agent-orchestrator Last Updated: 2026-02-25 | Version 1.3.0 (Speed-First) ### Cloud Integration (Requires Setup) The system supports optional cloud backup and sync: Supermemory Integration: Push memories to cloud for cross-device access Mem0 Auto-Fact Extraction: Automatic fact extraction from conversations (80% token reduction) Configure via environment variables: SUPERMEMORY_API_KEY - For cloud backup MEM0_API_KEY - For auto-fact extraction ### Optimization Techniques Implemented TechniqueLayerComplexityBenefitBloom FiltersPre-queryO(1)Skip expensive queriesRedis Hot CacheL0<1msSub-millisecond accessMem0 L1 CacheL1<10ms80% token reductionParallel QueriesAllO(1) wallConcurrent tier queriesConnection PoolingChromaDBReuseNo connection overheadBinary SearchGit-NotesO(log n)Fast sorted lookupsPre-computed EmbeddingsCacheSkip computeCache hits = instantLazy LoadingFilesOn-demandReduced memory footprintPre-fetch ContextPredictiveAnticipateResults ready before askResult CachingTTL1-5minAvoid redundant queries ### L1 Cache (Mem0) Purpose: First-layer cache for 80% token reduction How: Mem0 extracts facts from conversations automatically Benefit: Reduces context window usage while preserving key information ### Parallel Tier Query Purpose: Query all memory tiers simultaneously How: Async queries to Mem0, ChromaDB, Git-Notes, and file search Benefit: O(1) wall-clock time instead of sequential O(n) tier traversal ### Redis Hot Cache (L0) Purpose: Ultra-fast L0 cache for frequently accessed memories TTL: 5-15 minutes for hot data Benefit: Sub-millisecond access for top results ### Result Caching with TTL Purpose: Cache search results to avoid redundant queries TTL: 1-5 minutes depending on tier Benefit: Dramatically reduces API calls and computation ### Binary Search (Git-Notes) Purpose: O(log n) lookup in sorted memory index How: Maintain sorted timestamp/index files Benefit: Fast retrieval from large Git-Notes collections ### Connection Pooling Purpose: Reuse ChromaDB and Ollama connections How: Persistent connection pools with health checks Benefit: Eliminates connection overhead on each query ### Bloom Filters Purpose: Quick existence checks before expensive queries How: Probabilistic filter for memory presence Benefit: Skip unnecessary tier searches when result is definitely not present ### Pre-fetch Context Purpose: Predictive memory loading based on context How: Anticipate likely queries based on current session Benefit: Results ready before user asks ### Lazy Loading Purpose: Load files only when needed How: On-demand loading of large files Benefit: Reduced memory footprint and faster initial response ### Pre-computed Embeddings Purpose: Cache embeddings for frequently queried content How: Store embeddings alongside source data Benefit: Skip embedding computation on cache hit How: Store embeddings alongside source data Benefit: Skip embedding computation on cache hit ### Priority Order Mem0 (L1 Cache) → ChromaDB → Git-Notes → Supermemory (Backup) TierServicePurposeLatencyCostL0RedisHot cache<1msLowL1Mem0Auto-extracted facts<10msMediumL2ChromaDBSemantic vectors<50msLowL3Git-NotesKnowledge graph<20msFreeBackupSupermemoryOffsite backupDailyFree ### Cloud Services Integration Mem0 (L1 Cache) Purpose: First-layer cache for 80% token reduction How: Auto-extracts facts from conversations API: MEM0_API_KEY environment variable Benefit: Reduces context window usage while preserving key information ChromaDB (Vector Storage) Purpose: Semantic similarity search Embeddings: bge-m3 via Ollama Connection: Pooled connections for speed Fallback: Keyword search if unavailable Git-Notes (Knowledge Graph) Purpose: Structured JSON storage Lookup: Binary search O(log n) Sync: Git-based versioning Supermemory (Cloud Backup) Purpose: Daily backup only (not real-time sync) Frequency: Once per day API: SUPERMEMORY_API_KEY environment variable Benefit: Reduces API calls while maintaining offsite backup ### Environment Variables # Required for cloud features MEM0_API_KEY=your_mem0_key # Auto-fact extraction SUPERMEMORY_API_KEY=your_key # Cloud backup # Optional overrides CHROMA_URL=http://localhost:8100 # ChromaDB server OLLAMA_URL=http://localhost:11434 # Ollama server EMBEDDING_MODEL=bge-m3 # Embedding model ### Search Priority Flow (v1.0.5) Query Input │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 1. BLOOM FILTER CHECK (O(1)) │ │ • Probabilistic existence check │ │ • Skip expensive queries if definitely not present │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 2. REDIS HOT CACHE / L0 CACHE (Sub-millisecond) │ │ • TTL: 5-15 minutes │ │ • Frequently accessed memories │ │ • Return immediately if cached │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 3. MEM0 L1 CACHE (First Priority) │ │ • Auto-extracted facts (80% token reduction) │ │ • Fast fact lookup │ │ • No embedding computation needed │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 4. CHROMADB (Second Priority) │ │ • Semantic vector search (bge-m3 embeddings) │ │ • Connection pooling for speed │ │ • Return top-k results with scores │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 5. GIT-NOTES (Third Priority) │ │ • Structured JSON knowledge graph │ │ • Binary search on sorted index │ │ • O(log n) lookup time │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ 6. FILE SEARCH (Fallback) │ │ • Raw grep on daily/diary files │ │ • Last resort fallback │ └──────────────────────────────────────────────────────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ RESULTS MERGE & RANKING │ │ • Combine results from all tiers │ │ • Apply importance weights (Hippocampus) │ │ • Apply emotional relevance (Amygdala) │ │ • Apply value scores (VTA) │ │ • Return unified ranked results │ └──────────────────────────────────────────────────────────────┘ ### Cache Strategy Details Cache Hit: Return cached result immediately (sub-ms) Cache Miss: Query next tier, cache result with TTL Negative Cache: Optionally cache "not found" results (shorter TTL) Cache Invalidation: On session end, new memory add, or manual trigger ### Required Services (must be running) ChromaDB on http://localhost:8100 Ollama on http://localhost:11434 with bge-m3 model ### Optional Services (require API keys) Mem0.ai account (for cloud fact extraction) Supermemory.ai account (for cloud backup) Redis (optional, falls back to in-memory) ### Environment Setup Copy .env.example to .env Fill in optional API keys if using cloud features Run python3 cli.py --help to get started ### Manual Setup for Automation The CLI provides commands but cron jobs are NOT auto-installed. To enable: Add cron jobs manually via crontab -e Example: 0 3 * * * python3 /path/to/cli.py cloud sync ### On-Import Side Effects When Python imports cli.py, it may create memory directories under ~/.openclaw/memory/. This is intentional - the system needs these directories to function. To avoid this, run commands via subprocess rather than import. ### No Auto-Installed Cron Jobs The skill provides CLI commands for automation but does NOT auto-install cron jobs. You must manually add them if desired: # Add to crontab -e 0 3 * * * python3 /path/to/cli.py cloud sync ### Cloud Features Cloud features (Mem0, Supermemory) require API keys. Set in environment or .env file before use. ### When Network Access Occurs VariableWhen AccessedExternal ServiceCHROMA_URLIf setChromaDB serverOLLAMA_URLIf setOllama serverMEM0_API_KEYIf set AND MEM0_USE_LOCAL=falseMem0.ai APISUPERMEMORY_API_KEYIf setSupermemory.ai APIREDIS_URLIf setRedis server ### Default Behavior (No Network) Without API keys, system runs fully offline Uses local ChromaDB + local Ollama (if available) All data stored locally in ~/.openclaw/memory/ ### Cloud Features Only enabled when you: Set MEM0_API_KEY and set MEM0_USE_LOCAL=false Set SUPERMEMORY_API_KEY These are opt-in only. Default = offline. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: Broedkrummen - Version: 1.9.5 ## Source health - Status: unstable - Item is unstable. - This item is timing out or returning errors right now. Review the source page and try again later. - Health scope: item - Reason: timeout - Checked at: 2026-05-06T19:23:29.241Z - Expires at: 2026-05-07T07:23:29.241Z - Recommended action: Review source status ## Links - [Detail page](https://openagent3.xyz/skills/overkill-memory-system) - [Send to Agent page](https://openagent3.xyz/skills/overkill-memory-system/agent) - [JSON manifest](https://openagent3.xyz/skills/overkill-memory-system/agent.json) - [Markdown brief](https://openagent3.xyz/skills/overkill-memory-system/agent.md) - [Download page](https://openagent3.xyz/downloads/overkill-memory-system)