dbs-decision

The dbs-decision skill is a personal decision and knowledge management system designed to transform any long-running domain—such as business, health, career, learning, relationships, or investments—into a structured local knowledge project. It addresses the core problem of conversational systems losing context over time: decisions, observations, and reasoning can become fragmented or forgotten as chat history changes. By enforcing a persistent, file-based structure, this skill ensures that important information remains continuously usable and traceable across sessions.

The system is built around a four-layer architecture that separates information into facts, emergent patterns, snapshots, and unresolved questions. It emphasizes immutable records, where historical states are never overwritten but instead extended through timestamped annotations or new files. It also introduces strict source tagging rules to distinguish factual input, inferred judgments, and evaluated outcomes. In addition, it defines operational modes such as initialization, state updates, decision registration, result backfilling, and periodic state snapshots. These modes ensure that evolving information is consistently organized and that insights can be traced back to their origin without contamination from later hindsight.

This skill is intended for users managing complex, evolving domains that require structured thinking over time. It is especially useful for researchers, operators, founders, analysts, or individuals conducting long-term personal planning. Rather than acting as a decision-maker, the system functions as a durable cognitive scaffold that helps users track facts, refine mental models, and review decision evolution. Its design supports continuity, reflection, and accumulation of structured knowledge across time, making it suitable for any scenario where decisions must be revisited and understood in context.