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The context-retrieval skill empowers AI agents by providing access to a modular Rust-based self-learning memory system. It allows Claude to draw upon historical data, including past successes, failures, and implementation patterns, to make more informed decisions during complex workflows. By leveraging semantic search via embeddings or deterministic keyword indexing through Turso and redb, the skill ensures that relevant context—such as heuristics, error resolutions, and proven tool sequences—is always available to optimize current task performance and avoid repeating past mistakes.
