Analyze CSV data and figures to draft Results sections with statistical reporting.
npx skills add https://github.com/sxg/science --skill results-interpreter
Please help me install this Agent Skill. Skill: results-interpreter Source: https://github.com/sxg/science/tree/main/plugins/writer/skills/results-interpreter Command: npx skills add https://github.com/sxg/science --skill results-interpreter
Researchers often have to translate raw CSV results and figure outputs into a cohesive, publication-ready Results section, preserving statistical accuracy and narrative flow.
Use the results-interpreter to analyze your project data by providing the data/results.csv and figures/ directory.
High-intent search queries and answers about installing and using this skill.
To draft a publication-ready Results section from CSV files and figures, you can use a data interpreter Skill. It analyzes your tabular data and visual outputs to generate a structured narrative with proper statistical reporting.
Converting descriptive statistics and p-values into a research narrative involves parsing CSV data and cross-referencing figures. This process aligns your statistical findings with project scope documentation to produce cohesive results notes.
To interpret data visuals and align them with CSV outputs, you need a tool that cross-references figures against tabular results. This ensures your visual descriptions match the extracted confidence intervals and p-values accurately.
Yes, analyzing CSV results and generating figures interpretation requires a specific setup. You need a data folder containing CSV files, a figures folder with images, and a defined scope.md file to guide the interpretation process.
Yes, you can use this method to flag ambiguities when writing statistical results from data files. The interpretation process includes quality checks that pause for user confirmation to prevent misinterpretation of your data.
Data-to-narrative conversion requires a scope.md file to guide the interpretation of your statistics and figures. It ensures the generated Results section aligns precisely with your project scope documentation and research objectives.
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