What problem does it solve?
Template authors and reviewers often face inconsistent field names, mixed-language content, overly dense component schemas, and improper hypergraph grouping that lead to extraction errors and poor downstream quality. Manual inspection is time-consuming and error-prone, and subtle schema/guideline conflation causes ambiguous extractor behavior.
Core Features & Use Cases
- YAML Parsing & Validation: Load and validate template structure to detect syntax and structural problems.
- Rule-based Analysis: Identify naming standard violations, multilingual inconsistencies, excessive field counts, schema-vs-guideline repetition, and hypergraph grouping anti-patterns.
- Auto-fix & Suggestions: Apply safe automatic renames and language separations, suggest simplifications for dense components, and mark design decisions for review.
- Reporting & Integration: Produce an actionable optimization report for batch operations, pre-validator checks, template reviews, and iterative template evolution.
Quick Start
Run the template optimizer on a YAML template to automatically detect issues, apply safe fixes where appropriate, and produce a clear optimization report.