Use when a user wants cross-session personal context shared by compatible AI agents, or asks to load, save, inspect, archive, recover, clean up, or upgrade l...

Get comprehensive context about a location including nearby places, area description, and optional weather. Use when you need to understand what's around a l...

Memory management system powered by ReMe. Enables cross-session memory persistence, automatic user preference application, and intelligent context compressio...

v3.1 (ClawHub-safe, source-verified): OpenClaw context memory optimizer. Prevents context overflow, memory drift, and token waste in long agent sessions. Bas...

Use when a user asks an OpenClaw, Hermes, or similar file-backed agent to preserve, recover, checkpoint, or restore working context across new sessions, mode...

Dynamic context preprocessor for OpenClaw agents. Selects relevant memory, collapses timelines, detects forbidden patterns, and injects task-specific context...

Persistent context survival for OpenClaw. Writes file-based anchors to memory/anchors/ to preserve critical context across sessions. Reads MEMORY.md and dail...

Prevent context overflow with automatic session truncation and memory preservation.

Continuous session event recording for inter-session memory survival. Use when you want to persist conversation context between sessions, prevent memory loss...

Deterministic memory/context pipeline with semantic retrieval checks, compression/lint, safe fallback, and memory watchdog.

Maintains and transfers context across sessions, models, and time to avoid repeating information on every new interaction or model switch.

Skill that restores conversation context when users want to "continue where we left off".

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.

Fetches recent Telegram messages at session start to maintain conversation context across sessions, with toggle and manual fetch commands.

Responsible for maintaining SKILLMEMORY.md in the target skill directory, recording the three most recent execution pipeline JSONs, and modifying the descrip...

Your AI agents start from zero. Every session. Users repeat themselves — their stack, their preferences, their ongoing projects. Threadline fixes this in 2 l...

Memory management system with automated tiered storage (hot/warm/gist/forgotten), time-decay organization, promotion engine, layer-search protocol, and sessi...

Pure Python memory manager for preserving and retrieving multi-layered AI memories across sessions, topics, and time without external dependencies.

Agent Memory for Commerce. Build commerce agents that remember customers, maintain transaction state across sessions, and reconcile billing context at scale...

Comprehensive memory management optimization for AI agents. Use when: (1) Agent experiences context compression amnesia, (2) Need to rebuild context quickly...

Transfer memory files from one OpenClaw agent to another. Use when you need to migrate memory, configuration, or context from one agent to another agent.

Ultimate memory optimization for AI agents. Combines WAL protocol, Working Buffer, three-tier memory (HOT/WARM/COLD), context budgeting (10/40/20/20), and .l...

Self-improving AI memory system with intelligent context injection and adaptive learning

Use when a project's project memory file is over ~300 lines, when starting a new project from scratch, or when the user mentions context bloat, lost env URLs...

Keep an LLM agent's long-term memory healthy — the cure for context rot. Use when a memory store exists and the user wants to check or tidy it ("记忆体检", "整理记忆...

Detect and recover from context resets, memory/index outages, and cache clears with deterministic, trust-preserving reconstruction. Use when continuity break...

Structured task snapshot and automatic post-compaction recovery. Captures exact code, decisions, file paths, and task state before context compaction and rec...

Injects recent conversations from Telegram and Discord into the OpenClaw gateway session context. Enables the agent to remember and reference cross-platform...

Logs all OpenClaw conversations and events with role tags, saving to JSONL and Memvid for full context search and monthly sharded or single-file storage.

Gives the agent persistent, structured long-term memory across sessions. Organizes memory by project, client, trade, and domain. The agent never forgets what...

Stop your AI agent from forgetting everything between sessions. Three-tier memory architecture (long-term owner namespace / daily logs / session handoff), cr...

Universal AI memory infrastructure that stores, understands, and learns from past interactions. Works across ChatGPT, Claude, Gemini, DeepSeek, and any AI mo...

Gives your OpenClaw agent persistent memory across every session. MEMORIA maintains a structured knowledge layer: who you are, what you're building, every de...

Organize, compress, and curate OpenClaw memory without polluting permanent memory. Use when the user wants to compress memory files, clean dated memory notes...

Configure OpenClaw agent memory to survive compaction and session restarts. Use when: (1) setting up a new OpenClaw agent or workspace, (2) agents are forget...

AI Memory System with LLM Wiki

Total recall, 90% fewer tokens. Open source OpenClaw memory plugin — 5-engine local search, structured fact extraction, smart dedup, cross-agent sharing, and...

Memory system v4.13: Dual-layer structure (todos for execution + knowledge for strategy) with Dream/Refinement memory mechanisms.

Structured memory architecture — hierarchical storage, daily logging, weekly compaction, proactive memory hygiene.

Use this skill when you need to understand the architecture of a codebase, perform semantic searches across files, map dependencies before refactoring, or in...

Makes agent corrections persistent and reusable. When you override, reject, or correct an agent's output, this skill logs the correction and automatically in...

Make Claude, Cursor, Cline, Continue, and Zed remember every AI conversation forever — one local SQLite corpus shared across all of them. Installs memex (loc...

Indexed by skills.sh from johnlindquist/claude

Long-term memory, learning, and self-evolution for the agent. Activates on session start (SOUL.md/USER.md context), after significant decisions, on feedback,...

Indestructible agent memory — permanently stored, never lost. Save decisions, identity, and context as a memory chain on the Autonomys Network. Rebuild your...

Production-grade memory system for OpenClaw agents. Auto-organizes notes into topic files, prevents context loss during compaction, and runs daily/weekly mai...

Manages AI assistant long-term memory with layered storage for facts, events, skills, context, and fast indexing, including backup and integrity tools.

Core memory resilience layer: WAL (Write-Ahead Log), Working Buffer, and three-layer memory integration. Prevents context loss during compaction and ensures...

Fast semantic search for AI agent memory files using TF-IDF and SQLite. Enables instant context retrieval from MEMORY.md or any markdown documentation. Use when the agent needs to (1) Find relevant context before starting a task, (2) Search through large memory files efficient…

Structured long-term memory management engine with multi-role isolation, layered indexing, and strict context retrieval protocols to prevent token waste and...

A cross-agent memory and context SDK for AI systems. Provides structured context injection, conversation memory portability, and context enrichment.

OpenClaw wrapper for Muratcan Koylan's Agent Skills for Context Engineering. 13 skills covering context optimization, multi-agent patterns, memory systems, t...

Recover from context compaction by scanning memory files and surfacing where you left off. Use when waking up fresh, after compaction, or when you feel lost about what you were doing.

Use this skill when managing long-context conversations and tasks. Provides intelligent compression, key extraction, context enhancement, memory retrieval, a...

Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences "memory loss" after compaction, or when aiming to reduce t…

Analyze and archive low-value memory notes in OpenClaw workspace to reduce context bloat and improve responsiveness. 适用于上下文冗余、维护整理场景；默认流程为 analyze → plan → c...

Automates context monitoring by summarizing history, saving to long-term memory, and sending QQ alerts when session message or token limits approach threshold.

Audit and slim down always-loaded context files (AGENTS.md, TOOLS.md, USER.md, MEMORY.md, HEARTBEAT.md, SOUL.md, IDENTITY.md). Use when asked to reduce token usage, audit context files, optimize context window, or slim down workspace files. Measures current token cost and iden…

Diagnose and optimize an OpenClaw agent workspace's injected context files (AGENTS.md, SOUL.md, USER.md, MEMORY.md, TOOLS.md, HEARTBEAT.md, etc.) to reduce p...

Optimize context window usage by summarizing old conversation segments, extracting key facts and decisions to permanent memory, and keeping current context l...

Optimizes context window via MECW principles and memory tiering

Project-based agent context management system for maintaining long-term memory and project state across sessions. Use when starting or continuing any softwar...

Compress conversation context into a TurboQuant vector store inside OpenClaw memory, then retrieve the most relevant entries on demand to stay within token b...

Diagnose always-loaded workspace context files such as AGENTS.md, SOUL.md, USER.md, MEMORY.md, and TOOLS.md. Use when you want to reduce context bloat, detec...

Buildable Bring Your Own Context system for AI agents. Use for: creating user-owned or org-owned context vaults, scaffolding typed memory systems, generating...

ContextKeeper — Safe project state tracking for AI agents. Manual checkpoint creation with validated inputs. No background processes, no PID manipulation, no...

A persistent local-only memory system for AI coding agents. Two files, one idea — AGENTS.md (committed, shared) + .agents.local.md (gitignored, personal). Agents read both at session start, update the scratchpad at session end, and promote stable patterns over time. Works acro…

A persistent local-only memory system for AI coding agents. Two files, one idea — AGENTS.md (committed, shared) + .agents.local.md (gitignored, personal). Agents read both at session start, update the scratchpad at session end, and promote stable patterns over time. Works acro…

Solves the memory fragmentation problem for Agents during session restarts, sub-agent boundaries, and cron/heartbeat isolation.

Use when: you chat across topics and want explicit boundaries to prevent topic bleed. Tags: [ISO], [SCOPE], [GLOBAL], [NOMEM], [REM]. (Memory tags are signal...

ALWAYS use this skill (never memory_search or exec alone) when the user asks about coding sessions, recent dev work, project briefings, or developer notes. T...

🧠 Long-term memory system for OpenClaw agents. Manages entities, context, and knowledge base with Obsidian integration. By AB-Agents (Alex Burr).

Unlimited organized memory for your AI agent. Store, search, and organize projects, contacts, decisions, and knowledge across categories. Never lose context...

Hierarchical memory management for AI agents across sessions. Maintains three layers — daily notes (raw logs), active context (working memory), and long-term...

Universal memory architecture for AI agents. Provides long-term memory, daily logs, diary, cron inbox, heartbeat state tracking, social platform post tracking, sub-agent context patterns, and adaptive learning -- everything an agent needs for identity continuity across sessions.

Solve the "agent forgot everything" problem with search-first protocol, automated memory sync, and context preservation. No more conversation restarts!

Design a persistent memory architecture for AI agents that survives context windows and session resets. Use when building long-running agents, personal assis...

Scalable memory system for AI agents with short-term, long-term, and episodic memory. Use when building agent memory persistence, conversation context manage...

Set up the full OpenClaw agent memory system with 3-tier memory (HOT/WARM/COLD), daily logs, semantic search (QMD), and lossless context management (Lossless...

Persistent memory system enabling AI agents to remember facts, learn from experiences, and track entities across sessions for improved context awareness.

Tiered memory system for OpenClaw agents. Gives agents instant context on startup with a 4-line state snapshot (L0) and 7-day rolling context (L1). Eliminate...

Long-term memory systems for AI agents. Implements vector memory, entity tracking, conversation summarization, and persistent context across sessions.

Never lose context again. The Write-Ahead Log (WAL) protocol with SESSION-STATE.md gives your agent bulletproof memory that survives compaction, restarts, an...

Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure m...

Long-term memory via ChromaDB with local Ollama embeddings. Auto-recall injects relevant context every turn. No cloud APIs required — fully self-hosted.

Tiered memory system for OpenClaw agents. Gives agents instant context on startup with a 4-line state snapshot (L0) and 7-day rolling context (L1). Eliminate...

Automatically syncs and maintains detailed conversation logs and activity digests across agent sessions for persistent memory and context recall.

Cross-platform persistent memory hub connecting Codex, OpenClaw, and Claude Code workflows into a unified Obsidian-based knowledge base. Supports daily work logs, task tracking, decision records, and project context sharing across AI coding agents. Templates and configuration …

Persistent memory system for AI agents to remember facts, learn from experience, track entities, and recall context across sessions.

Recall and persist the user's long-term context with DogearAI — their personal, cross-tool AI memory layer. Use at the start of any task that needs the user's saved context (their preferences, past decisions, project background, stack), and whenever the user states something d…

File-based memory system for AI agents that forget between sessions. Implements the "Dory-Proof" pattern for continuity across context resets. Use when setting up agent memory, building workspace structure, implementing task tracking, or preventing context-loss errors. Trigger…

FastAPI personalization webhook that adds persistent caller memory and dynamic context injection to ElevenLabs Conversational AI agents on Twilio. No audio p...

Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vib...

Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vib...

Persistent session memory system that prevents knowledge loss after context compaction. Converts session transcripts to searchable Markdown, builds an auto-u...

FocalPoint — AI cognitive operating system. Memory + attention management + workflow orchestration. Workbench prepares context before tasks. Three-Province r...

Automated hierarchical memory compression system that prevents context overflow through daily→weekly→monthly→core compression. Use when you need (1) long-ter...

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.

Persistent cross-session memory for your agent, powered by HMR (Hestia Memory Runtime). Save important facts and preferences, recall relevant context, and re...