Clawtex

Clawtex addresses the common issue of AI agents losing track of prior interactions by maintaining distinct layers of information. The state component tracks active entities such as projects and goals in a queryable format. Events capture timestamped actions and decisions, while lessons identify recurring patterns to create enforceable guidelines that reduce repeated errors. Users connect the service through standard settings in Claude platforms or via local installation. Once active, the system loads context on demand and supports tools for logging new information or querying past records. Over time, analysis of accumulated events generates structured improvements that agents apply in future sessions. This approach differs from simple text storage by keeping each memory type separate and structured for reliable retrieval. It supports individual and team usage with options for scaling the number of agents and extending history retention.