Store and retrieve persistent AI memories with vector search and write-ahead logging.
npx skills add https://github.com/wbin0001/Memory-Compass --skill memory-compass
Please help me install this Agent Skill. Skill: memory-compass Source: https://github.com/wbin0001/Memory-Compass/tree/main Command: npx skills add https://github.com/wbin0001/Memory-Compass --skill memory-compass
Memory Compass stores and retrieves persistent AI memories with fast semantic search, reliable write-ahead logging, and checkpoint-based recovery.
Save a checkpoint for the current task and recover it later.
High-intent search queries and answers about installing and using this skill.
Persistent AI memory stores and retrieves context across sessions using LanceDB for fast semantic vector search. This enables agents to remember task progress and decisions without losing state between interactions.
Checkpoint-based recovery saves task state at specific intervals, allowing long-running AI tasks to resume from the last saved point after a failure. This prevents complete context loss and reduces redundant computations.
Memory context is lost without durable storage mechanisms. A file-system write-ahead logging (WAL) ensures traceability and durability, recording context changes before applying them to prevent data loss during faults.
A unified search interface routes queries across multiple memory tracks, aggregating results for robust retrieval. This approach ensures comprehensive semantic searches across all stored AI memories.
Yes, LanceDB enables high-speed semantic memory retrieval by indexing AI memories as vectors. It allows fast cross-session recall by matching query embeddings against stored memory vectors.
Write-ahead logging (WAL) provides fault tolerance by recording memory operations to a file-system log before execution. If a failure occurs, the log replays uncommitted operations, ensuring reliable memory restoration.
dglijin-ossStore and search memories locally using LanceDB and Ollama embeddings.
X-McKaySearch hierarchical memory tiers and return relevance-ranked results.
arbazkhan971Design and validate autonomous AI agents with tool orchestration and guardrails.
eyadsibaiImplement persistent memory systems for AI agents using knowledge graphs.
