Observe conversations, compress notes, and consolidate memory across sessions.
npx skills add https://github.com/gavdalf/total-recall --skill total-recall-gavdalf
Please help me install this Agent Skill. Skill: total-recall Source: https://github.com/gavdalf/total-recall/tree/main Command: npx skills add https://github.com/gavdalf/total-recall --skill total-recall-gavdalf
This Skill provides autonomous memory for AI agents, automatically observing conversations, compressing them into prioritized notes, consolidating when they grow, and recovering anything missed, ensuring no conversation is lost.
Use the total-recall skill to observe the current conversation and save important details.
High-intent search queries and answers about installing and using this skill.
To add autonomous memory to an AI agent, you need a system that observes conversations, compresses them into prioritized notes, and consolidates data for session recovery. This ensures conversation context persists across resets.
AI agent memory consolidation works by automatically merging and compressing prioritized notes when they grow too large, archiving stale items to maintain accessible context without losing important facts or decisions.
Yes, you can recover missed observations after a manual session reset. The autonomous memory system automatically recovers any missed data during resets to ensure conversation continuity and data persistence.
Yes, you need LLM API access to compress and consolidate AI agent memory. The system requires LLM API access specifically for observation compression and memory consolidation tasks to function properly.
Setting up autonomous memory for AI agents requires jq, curl, python3, and PyYAML. These dependencies support the scripts and components needed for observation, compression, and session recovery.
AI agents lose context after restarting because they lack persistent memory. You can prevent this by using an autonomous memory system that observes conversations, saves key information, and recovers missed data across sessions.
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