Prevent context loss during LLM compaction via Write-Ahead Logging (WAL), Working Buffer, and automatic recovery. Three mechanisms that ensure critical state...

Actively monitors token utilization and executes memory compaction routines before context bloat causes failures.

Background memory compaction with auto-trigger, chat summary paragraph, configurable threshold, model selector, settings tab, and result storage for OpenClaw...

Production token thresholds, circuit breaker, and compaction sequence from production Claude Code deployments. Eliminates context death spirals permanently.

Learn to recognize and prevent context death spirals in OpenClaw agents. Covers symptoms, root causes, configuration categories, and why most default setups...

19 production-hardened patterns for AI agents — memory, verification, ambiguity handling, compaction survival, delegation, proof-based handoffs, stale-worker...

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

Searchable conversation memory that survives context compaction. Indexes session transcripts into SQLite with full-text and semantic search so your agent can...

Your OpenClaw agent forgets everything between sessions — after /new, after compaction, after overnight. Clever Compact fixes all three: injects your last st...

Ultra-light automatic handoff manager for long-running agent sessions at context-boundary moments. Use this skill when a runtime reports context compaction/s...

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

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...

Progressive memory management with categorized files, indexed retrieval, and survival-merge evolution. Prevents AI amnesia after context compaction. Activate...

AetherCore v3.3.4 - Security-focused final release. High-performance JSON optimization with universal smart indexing for all file types. All security review...

Proactively updates a concise session summary every 15 turns or on tool loops to manage context size and preserve key decisions and progress.

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

Automatic context compression for OpenClaw sessions. Summarizes long conversations into structured digests (decisions, facts, pending items, technical detail...

The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into priorit...

This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding…

Output validation gates for AI agent systems. Prevents hallucinated data, leaked internal context, wrong formats, duplicate sends, post-compaction drift, and...

Reduce Anthropic API costs (cache read, compaction, context bloat) for OpenClaw agents. Use when users ask about token optimization, reducing API costs, cach...

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

Persistent, semantic memory for AI agents. Gives your AI long-term recall that survives compaction and session resets — 98% accuracy, 20ms latency.

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

Your agent forgets everything after compaction? This fixes it. Built by the AI Advantage community — the world's leading AI learning platform (aiadvantage.ai...

Smart context compaction for OpenClaw agents. 4-phase progressive strategy: Scan, Extract, Check, Compact. Before running /compact, this skill scans tool out...

Generates structured, concise memory summaries during flush or compaction, detailing conversation stats, tools, user requests, tasks, files, progress, and ti...

Smart context compaction for OpenClaw agents. 4-phase progressive strategy: Scan, Extract, Check, Compact. Before running /compact, this skill scans tool out...

Detect behavioral drift in persistent AI agents after context compression events. Use when a long-running agent has compressed its context (compaction, trunc...

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.

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…

Token-based context compaction for local models (MLX, llama.cpp, Ollama) that don't report context limits.

Manage AI agent context window consumption, prevent compaction death spirals, and enforce sub-agent spawn policies. Use when: (1) context is filling up and w...

Automatically recover working context after session compaction or when continuation is implied but context is missing. Works across Discord, Slack, Telegram,...

Scan your OpenClaw workspace for truncation risks, compaction anchor health, workspace hygiene, and drift tracking over time. Use when the operator asks to "...

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

Maintain persistent focus on active work across compactions and session restarts. Use when starting a multi-step project, when resuming after compaction, whe...

This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentio...

🧊 IceCube Memory — Local-first, zero-token-footprint memory architecture for AI agents. Real-time retrieval, four-layer hierarchy, compaction survival. Buil...

Preserve user-critical instructions across long sessions and context compaction. Use when users mark constraints as important/must/always/never/highest-prior...

Use Lethe persistent memory for startup orientation, recall, logging, flags, and session compaction.

AI agent fleet memory system — Qdrant + Mem0 + Neo4j/Graphiti. Composite scoring, compaction engine, temporal knowledge graph, multi-claw federation, sleep-t...

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

Complete memory management system for OpenClaw agents. Combines compaction-aware saving, a formal boot sequence, domain organization, memory scoring, structu...

Task management via Basic Memory schemas: create, track, and resume structured tasks that survive context compaction. Uses BM's schema system for uniform not...

Give an AI agent persistent semantic memory that survives restarts and compaction. Captures structured observations from tool calls, summarizes sessions (LLM...

Prevent memory loss in OpenClaw by adding a practical continuity and recovery layer that preserves active work across restarts, compaction, and crashes.

Proactive, self-improving agent architecture with hardened security. WAL Protocol, Working Buffer, Compaction Recovery, Autonomous Crons, and battle-tested p...

Manage, optimize, and troubleshoot the OpenClaw memory system — MEMORY.md curation, daily logs (memory/YYYY-MM-DD.md), memory_search tuning, compaction survi...

Diagnose and prevent OpenClaw agent failures — session bloat, lane deadlocks, bootstrap truncation, auth errors, compaction timeouts, and more. Use this skil...

Sets up a production-ready OpenClaw workspace with artifact workflows, secure secrets, memory compaction, and long-running agent patterns via one command.

Production-validated OpenClaw skills built for production Claude Code deployments. Compaction, loop termination, session memory, bash security, agent memory...

Generates an operational resume card before Claude context compaction — so the next session knows exactly where it left off, what mode it was in, and what to...

Transform AI agents from task-followers into proactive partners. Implements WAL Protocol, Working Buffer, Compaction Recovery, Unified Search, Security Harde...

Persistent memory engine for AI agents with semantic recall, hotness prioritization, importance weighting, time decay, and auto-compaction. Zero external dep...

Preserve conversation continuity across token compaction cycles by extracting and archiving all prompts with date-wise entries. Automatically triggers at 95% token usage (pre-compaction) and 1% (new sprint start) to export session history, then ingests archived summaries on se…

Enhanced self-improvement skill with FULL chat logging (text+images), smart memory compaction, automatic pattern recognition, context-aware learning, multi-s...

Context window health monitoring for OpenClaw agents — threshold warnings via Telegram, pre-compaction snapshots, and memory rotation.

Your agent forgets everything after compaction? This fixes it. Built by the AI Advantage community — the world's leading AI learning platform (aiadvantage.ai...

Automatically loads recent conversation memory into new sessions and generates AI summaries during compaction to maintain continuity across conversations. Pr...

Persistent session state management across compaction and restarts via lifecycle hooks

Task-based cross-session context management for OpenClaw agents. Maintains persistent task files so context survives session resets, compaction, and channel...

Monitors session context usage and saves checkpoints when approaching limits to prevent data loss before compaction or long tasks.

Smart context compaction for OpenClaw agents. 4-phase progressive strategy: Scan, Extract, Check, Compact. Before running /compact, this skill scans tool out...

Manual context compaction at logical workflow boundaries rather than arbitrary auto-compaction. Use after completing exploration phases, before switching maj...

Unified memory management combining auto-compaction, tiered storage, semantic recall, and token optimization for efficient, lossless context handling in Open...

Task decomposition and execution framework for Claude — breaks complex work into verified subtasks, plants context anchors to survive compaction, and never l...

Smart context compaction for OpenClaw agents. 4-phase progressive strategy: Scan, Extract, Check, Compact. Before running /compact, this skill scans tool out...

Session crash and compaction recovery using a two-file WAL (Write-Ahead Log) system. Use when setting up persistent memory for an OpenClaw agent that needs t...

Create managed Iceberg tables using Amazon S3 Tables (s3tables API namespace) with automatic compaction and snapshot management. Sets up table bucket, namespace, table, schema, Glue catalog registration, partitioning, IAM access control. Triggers on: create table, data lake ta…

Saves 20-40% of LLM tokens by teaching the agent to write compressed responses, compressed memory logs, and compressed pre-compaction summaries. Works via SO...

This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentio...

PostgreSQL-based structured memory system for OpenClaw agents with pre/post-compaction integration, dual-write capability, and full context preservation. Pri...

Distill successful multi-step OpenClaw sessions into reusable learned skills before compaction. Use when a task involved many tool calls, environment setup,...

Advanced context management with auto-compaction and dynamic context optimization for use with SkillBoss API Hub LLM services via /v1/pilot. Features intelli...

Use when a session is about to end with unfinished work, after context loss or compaction, after a crash, or when the user wants to resume a multi-step task....