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run-pipeline

Run the project's R pipeline and verify outputs have non-zero size.

Updated Feb 21, 2026
Search Tags:#automation#pipeline#data-analysis#r#quality-assurance#reproducibility#verify-outputs
One-click install
npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill run-pipeline-choi-jaehyun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: run-pipeline
Source: https://github.com/choi-jaehyun/jaehyun-claude-workflow/tree/main/.agents/skills/run-pipeline
Command: npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill run-pipeline-choi-jaehyun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill runs the project's R-based analysis pipeline and verifies that outputs exist and are non-empty, enabling reproducible results and quality checks.

Core Features & Use Cases

  • End-to-end pipeline execution: runs the default full pipeline (code/main.r) to reproduce results.
  • Output validation: checks outputs/tables and outputs/figures for non-zero size and expected files.
  • Ad-hoc execution: supports running a specific script via ARGUMENTS to validate isolated components.
  • Verification integration: can leverage the verifier skill at .agents/skills/verifier/SKILL.md to confirm correctness.

Quick Start

Run the pipeline with Rscript code/main.r by default and verify that all expected outputs have non-zero size.

Frequently Asked Questions about run-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run an R pipeline and verify that all output files exist?▼

To run an R pipeline and verify outputs, execute the default script code/main.r using Rscript. The process checks outputs/tables and outputs/figures to ensure all generated files exist and have non-zero size for reproducible results.

Can I run a specific R script instead of the default main.r pipeline?▼

Yes, you can run a specific R script by providing the target script path through ARGUMENTS. This allows ad-hoc execution and validation of isolated pipeline components rather than running the full end-to-end analysis.

How do I check if my R analysis pipeline failed to generate outputs?▼

To check if your R analysis pipeline failed, review the reported script exit codes and any warnings or errors. The verification process confirms that expected files in outputs/tables and outputs/figures have non-zero size.

What is the best way to automate reproducibility checks for data analysis in R?▼

Automating reproducibility checks for data analysis in R involves executing the full pipeline end-to-end and validating output sizes. This approach reports script exit codes and errors to ensure the analysis consistently produces expected non-empty files.

Does this R pipeline runner integrate with existing verification tools?▼

Yes, the R pipeline runner can leverage the verifier skill located at .agents/skills/verifier/SKILL.md. This integration confirms output correctness after the pipeline executes and validates that all generated files are non-empty.

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