paper-plan

To convert experiment results into a structured paper outline, this skill extracts a Claims-Evidence Matrix from your narrative reports and experiment artifacts, then generates a venue-aware section plan with strict page budgets. It specifically targets ML submissions by planning sections around your validated claims.

Planning figures and citations for an academic paper outline involves generating a detailed figure plan with a hero figure and mapping explicit evidence sources to each section. This skill scaffolds your citation plan directly from the extracted Claims-Evidence Matrix to ensure claims are properly supported.

Yes, you can use this paper planning workflow for IEEE journal submissions because it applies venue-aware structure and page budgeting rules. It dynamically adjusts the section plan and MAX_PAGES constraints to fit different target publication contexts, including both ML conferences and IEEE formats.

A Claims-Evidence Matrix in academic writing is a structured mapping that links your research conclusions to specific experimental proof. This skill automatically extracts or generates this matrix from your experiment artifacts to drive the section-by-section narrative of your paper outline.

To identify missing evidence in a research paper outline, you can utilize the optional style-ref structural guidance feature to emit a GAP_REPORT.md. This report marks missing evidence slots within your planned sections without fabricating content, ensuring you know exactly what experiments are still needed.

To generate a venue-ready paper outline, you need narrative reports, auto-review conclusions, and experiment or figure artifacts present in your project directory. The skill specifically looks for files like NARRATIVE_REPORT.md and CLAIMS_FROM_RESULTS.md to build the structured PAPER_PLAN.md output.