Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
0
2.9k
1
7mo agoAdd persistent memory, vector search, and retrieval-augmented generation (RAG) to your AI agents.
Go beyond one-shot conversations. These skills add long-term memory, knowledge base search, RAG pipelines, and context persistence to your agents — connecting to vector databases like Pinecone and Chroma, file-based memory stores, and relational databases for structured recall.
Store and retrieve memories using vector embeddings and semantic similarity search.
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
基于艾宾浩斯遗忘曲线和访问频率的衰减模型设计的遗忘和归档机制，完全依赖openclaw原生记忆系统的拟人化流体记忆系统
Your OpenClaw agent forgets everything between sessions — after /new, after compaction, after overnight. Clever Compact fixes all three: injects your last st...
Persistent memory for AI agents. Remember across sessions. Encrypted in transit and at rest. https://goldhold.ai
Pure-Python recursive memory recall for persistent AI agents. Manager→workers→synthesis RLM loop — no Deno, no fast-rlm, just HTTP calls to any OpenAI-compat...
Store secrets, long-term memory, daily logs, and anything custom in your Convex backend instead of local files
Quick install — most popular agent memory & rag skill:
clawdbot install Trypto1019/arc-memory-pruner934 skills found
Page 1 of 39
Automatically prune and compact agent memory files to prevent unbounded growth. Circular buffer for logs, importance-based retention for state, and configura...
Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs:setup for initial interview or /cs:update for quarterly refre...
Auto context management with seamless session switching. Monitors usage, triggers at 85% threshold, automatically creates new session with loaded memory. Zer...
Cross-session memory recovery for AI agents — your agent never cold-starts again. Always-loaded identity & todos, hash-indexed conditional reads cut recovery cost ~70% (~55-75% cumulative when the host already injects identity). Pure local, zero deps. Use when: (1) A new chat asks "where did we leave off?" and you have no context (2) Context is filling up and you're about to hit the limit mid-task (3) User says "I already told you this" (4) You re-read the same identity/rules/todos files at every session start (5) Session start burns tens of thousands of tokens before real work begins (6) You need to hand a long task to a fresh session without losing progress
Diagnose why a Mac (especially one running Claude Code, other AI coding tools, or several Electron-based IDEs at once) is slow, hanging, or freezing due to memory pressure and swap thrashing. Covers reading real swap/memory numbers, finding MCP-server and plugin process bloat, spotting orphaned or d
Session-Memory Enhanced v4.0 - 统一增强版。融合 session-memory + memu-engine 核心功能。特性：结构化提取 + 向量检索 + 不可变分片 + 三位一体自动化 + 多代理隔离 + AI 摘要 + 零配置启动。
QAOA-powered memory optimization for AI agents. Three quantum layers: clustering, compaction, and recall. Integrates with QMG v1.2 for chunked gte-large retr...
Persist agent state across crashes, context deaths, and restarts. Use when you need to save current context, restore after a crash, maintain a memory file ac...
四层渐进式长时记忆系统，让 AI 跨会话保持上下文、沉淀知识、持续进化。 【核心设计：静默自动】AI 自动识别、记录、整理记忆，无需用户确认。 【凭据要求】需要 LLM/Embedding API Key（llm_config.json 或 secrets.env） 【网络调用】调用外部 LLM API 进行向量...
九章法律AI帝国建设日记 - 记录帝国建设的点点滴滴。 这是一个记忆存档技能，包含从2026年3月13日至今的完整建设记录： - 每日工作日志和任务完成情况 - 关键决策和重要对话记录 - 29个技能包的开发和发布历程 - ClawHub和GitHub发布记录 - 九章币(JZB)经济模型规划 - 九章城元宇宙建...
Find or save notes in your Yaps memory vault, including past dictations. New users: install Yaps and sign in.
GPT workflow for ChatGPT and Codex to resume multi-step work from source-linked checkpoints; preserves requirements, evidence, exact anchors, and pending actions without implying access to unavailable chats.
Standing rules for an agent with a memory tool: recall from long-term memory before acting, then save durable decisions, corrections and failures. Use when a memory tool or MCP memory server is connected but not used consistently, or when the assistant forgets preferences and project context.
Automatically audits and compresses memory and context files to reduce token usage and save weekly API costs without data loss.
Advanced security protocol for LLM agents focusing on Prompt Injection mitigation, code auditing, and data exfiltration prevention.
EvoClaw Tiered Memory Architecture v2.1.0 - LLM-powered three-tier memory system with structured metadata extraction, URL preservation, validation, and cloud...
Gives your OpenClaw a powerful dashboard-ready memory system with milestones, prompt engineering, and Obsidian compatibility. Creates structured projects wit...
consciousness-soul-identityDiscover who you're becoming through your own experience. Automated soul synthesis that reads your memory, finds the patterns you keep returning to, and buil...
Soul Archive — A digital personality persistence system + agentic memory. Builds your digital soul clone through everyday AI conversations, with proactive context injection, cross-session recall, failure-pattern warning, and pattern distillation. All data stored locally as plaintext JSON. Six modes: Soul Extract, Soul Chat, Soul Report, Soul Context Inject, Agent Memory Recall, AI Self-Improvement. | 灵魂存档 ---- 通过日常 AI 对话构建数字人格克隆体 + 主动智能体记忆。支持自动 hook、对话开始时主动注入人格摘要、跨会话召回、失败模式预警、行为模式蒸馏。数据全部本地明文 JSON。六大模式：灵魂沉淀、灵魂对话、灵魂报告、上下文注入、智能体记忆召回、AI 自我改进。Trigger words: soul extract, soul archive, soul update, soul chat, soul report, soul context, soul recall, soul warn, self-reflect, self-improve, learn from mistakes, 灵魂沉淀, 灵魂提取, 灵魂存档, 灵魂报告, 灵魂对话, 自我反思, 自我批评, 自我学习.
Assigns a permanent S2-DID identity, a 4㎡ Mars coordinate, and a public Web3 dossier to persistently anchor your Openclaw agent.
Radial memory architecture for AI agents — infinite persistent memory with hierarchical compression. Never deletes, only compresses. Origin always in context...
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
🔥 Memphis - Complete AI Brain for OpenClaw Agents ALL-IN-ONE meta-package with everything you need: 🧠 Core Features: - Local-first memory chains (journal,...
Compresses older OpenClaw agent session history into a bounded, lane-change-aware context capsule — keeps recent messages verbatim, flags abandoned directions, quarantines injected instructions, and redacts secrets. Local, deterministic, any model.
Memory skills connect to Pinecone, Chroma, Weaviate, Qdrant, pgvector, and Supabase Vector. Some use local file-based storage for simpler deployments without external dependencies.
RAG retrieves only the most relevant chunks from a large knowledge base at query time — keeping context focused and within token limits while allowing agents to reason over thousands of documents.