niwashi-slfg

Automated structured narrative generation orchestrates the full pipeline from stepwise discovery through harvesting, handling research, building, reviewing, and parallel execution autonomously. You simply provide a concept and optional audience to initiate the process.

Pipeline orchestration coordinates sequential phases including discovery, research, wireframing, and building, while applying dependency management, progress tracking, and safety checks to ensure structured narrative outputs are generated correctly.

Parallel builds and auto-correction loops are supported natively within the pipeline orchestration. The system applies configurable cycles and automated smoke testing to validate outputs and correct errors during the building phase.

Audience targeting and stepwise handoffs to human checkpoints are fully supported. You can configure the pipeline to pause at specific stages for human review while targeting the generated narrative toward a specific audience profile.

Pattern extraction and knowledge harvesting occur during the final pipeline phase, capturing reusable narrative structures from the completed outputs. This enables the discovery and storage of repeatable narrative patterns for future automated generation cycles.

Autonomous narrative orchestration relies on configurable cycles and automated loops, meaning complex or highly subjective concepts may require manual intervention at human checkpoints. Smoke testing validates structural integrity but cannot guarantee conceptual accuracy without human review.