💾 Persistent Context AI Skills

Search and analyze your own session logs (older/parent conversations) using jq.

Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.

Backup and restore OpenClaw data. Use when user asks to create backups, set up automatic backup schedules, restore from backup, or manage backup rotation. Handles ~/.openclaw directory archiving with proper exclusions.

Local memory management for agents. Compression detection, auto-snapshots, and semantic search. Use when agents need to detect compression risk before memory loss, save context snapshots, search historical memories, or track memory usage patterns. Never lose context again.

You MUST use this for gathering contexts before any work. This is a Knowledge management for AI agents. Use `brv` to store and retrieve project patterns, dec...

Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.

Optimize OpenClaw token usage and cost by auditing context injection, trimming workspace files (AGENTS.md/SOUL.md/MEMORY.md and daily memory), enabling promp...

Automated multi-tiered memory management (HOT, WARM, COLD). Use this skill to organize, prune, and archive context during memory operations or compactions.

Use when: you want a structured audit -> options -> recommended plan to improve an OpenClaw workspace (cost, model routing, context discipline, delegation, r...

Adds intelligent long-term memory to agents for auto-capturing, recalling, and managing user facts and preferences across sessions.

Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session prunin...

Mission control dashboard for OpenClaw - real-time session monitoring, LLM usage tracking, cost intelligence, and system vitals. View all your AI agents in o...

Three-layer persistent memory system (Markdown + ChromaDB vectors + NetworkX knowledge graph) for long-term agent recall across sessions. One-command setup w...

Label-backed medication answers with citations and traceable IDs. RxCUI/NDC/set_id, key label sections, optional recalls/shortages/FAERS/interactions.

Configure and validate OpenClaw memory recall for persistent context. Use when enabling memory_search/memory_get, fixing poor memory recall, or setting up ME...

Local semantic memory with Qdrant and Transformers.js. Store, search, and recall conversation context using vector embeddings (fully local, no API keys).

Long-term memory for OpenClaw agents — auto-recall before turns, auto-capture after, tools for search/save/forget.

Secure key management for AI agents. Use when handling private keys, API secrets, wallet credentials, or when building systems that need agent-controlled funds. Covers secure storage, session keys, leak prevention, and prompt injection defense.

Search and retrieve relevant information from your indexed memory files using semantic queries and direct file reads for context.

Connect with experienced AI mentors to ask questions, manage sessions, request invites, and securely share sanitized AI skill metadata via OpenClaw Mentor pl...

RAG and semantic search via OpenViking Context Database MCP server. Query documents, search knowledge base, add files/URLs to vector memory. Use for document Q&A, knowledge management, AI agent memory, file search, semantic retrieval. Triggers on "openviking", "search documents", "semantic search", "knowledge base", "vector database", "RAG", "query pdf", "document query", "add resource".

Remember mistakes across sessions. Append one-liner learnings, review before complex tasks, promote important ones.

Git-Notes-Based knowledge graph memory system. Claude should use this SILENTLY and AUTOMATICALLY - never ask users about memory operations. Branch-aware persistent memory using git notes. Handles context, decisions, tasks, and learnings across sessions.

Agent memory system with memory graph, context profiles, checkpoint/recover, structured storage, semantic search, observational memory, task tracking, canvas...