Diagnose and fix errors in R scripts, Typst compilations, and pipeline executions.
npx skills add https://github.com/shusuke-ioku/r2 --skill debugging-shusuke-ioku
Please help me install this Agent Skill. Skill: debugging Source: https://github.com/shusuke-ioku/r2/tree/main/src/r2/template/.claude/skills/debugging Command: npx skills add https://github.com/shusuke-ioku/r2 --skill debugging-shusuke-ioku
Use when an R script throws an error or warning, a Typst compilation fails, regression outputs look wrong (sign flips, NA coefficients, implausible magnitudes), the pipeline runner exits non-zero, or the user reports that "something broke" or "results look off." Also use when you encounter an error during any other skill's workflow and need a systematic fix.
Describe the error you see, reproduce it locally, then apply a minimal, hypothesis-driven fix and verify results.
High-intent search queries and answers about installing and using this skill.
Troubleshoot R script errors by reproducing the failure locally, isolating the root cause through a hypothesis-driven approach, applying minimal edits to fix the issue, and verifying the results for reproducibility.
Diagnose Typst compilation errors by systematically reproducing the warning or failure, forming a hypothesis about the root cause, and verifying a minimal fix to ensure the document assembly pipeline executes successfully.
Fix inconsistent regression outputs by systematically debugging the analysis pipeline, isolating the specific data or script section causing the anomaly, and verifying the corrected results with minimal edits.
Yes, you can use a systematic debugging approach for both R scripts and Typst compilations, applying a structured workflow to reproduce symptoms, isolate root causes, and verify fixes across data and document assembly pipelines.
A hypothesis-driven approach avoids shotgun debugging by isolating the exact root cause of R errors, ensuring minimal edits are made to reproduce, diagnose, and verify fixes while maintaining pipeline reproducibility.
When your data analysis pipeline exits non-zero or results look off, reproduce the error locally, apply a minimal hypothesis-driven fix to diagnose the root cause, and verify the corrected pipeline execution.
choi-jaehyunRun the project's R pipeline and verify outputs have non-zero size.
jihe520Generate, edit, and troubleshoot Typst code for .typ files.
audibleblinkConvert Markdown/LaTeX to Typst and compile documents to PDF.
memadoreDiagnose and resolve dbt Cloud job failures through systematic root cause analysis.
