What problem does it solve? Deep research workflows produce many scattered JSON result files with inconsistent structures and uncertain values, making it hard to assemble a readable, complete summary report manually. ## Core Features & Use Cases - Automated Report Generation: Scans all JSON results in the research output directory and generates a markdown report with a table of contents and detailed sections grouped by field category. - Uncertainty Filtering: Skips fields marked with [uncertain], listed in the uncertain array, or empty, so the report only contains confident values. - Flexible Structure Handling: Supports both flat and nested JSON structures with bilingual (Chinese/English) category mapping, plus user-selected summary fields shown in the TOC. - Use Case: After running deep research on 20 AI coding tools, invoke this Skill to produce report.md with an anchored TOC showing stars and citations per tool, followed by full categorized details. ## Quick Start Run /research-report in the directory containing your research outline.yaml and JSON results to generate the summary report.
