heady-task-genome

Task decomposition breaks complex projects into atomic units. A dependency graph maps these structural relationships, enabling consistent planning, execution tracking, and workflow optimization across coding, data, research, and operations domains.

Design a task schema by defining required fields including id, name, timestamps, classification, resources, and execution history. This formal structure captures task DNA, standardizes templates, and establishes taxonomy across multiple domains.

Yes, task genome mapping applies universally to coding, data, research, and operations domains. It standardizes decomposition rules and templates, allowing consistent modeling of task structure, dependencies, and lineage regardless of the specific domain.

Analyze execution history stored within the task schema to identify bottlenecks and estimate effort. Reviewing lineage data reveals performance patterns, improving future workflows and enabling similarity engines to surface reusable templates.

Yes, defining taxonomy and decomposition rules is required before template creation. These rules standardize how complex epics break into atomic units, ensuring resulting templates maintain structural consistency and accurate dependency mapping.