Killer-Skills Review
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Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.
Ideal for Data Science Agents focused on empirical economics research needing automated R script validation. Code review for R scripts checking reproducibility, correctness, and conventions
Core Value
Empowers agents to ensure reproducibility and correctness in R scripts or QMD chapters by checking for set.seed() presence, absolute paths, and deterministic data loading, leveraging libraries and protocols like library() calls and caching for web scraping.
Ideal Agent Persona
Ideal for Data Science Agents focused on empirical economics research needing automated R script validation.
↓ Capabilities Granted for review-r
! Prerequisites & Limits
- Requires access to .R or .qmd files
- Limited to R scripts and QMD chapters
- Does not support web scraping without caching
Source Boundary
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Decide The Next Action Before You Keep Reading Repository Material
Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.
Start With Installation And Validation
If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Cross-Check Against Trusted Picks
If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Move To Workflow Collections For Team Rollout
When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
Browser Sandbox Environment
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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.
FAQ & Installation Steps
These questions and steps mirror the structured data on this page for better search understanding.
? Frequently Asked Questions
What is review-r?
Ideal for Data Science Agents focused on empirical economics research needing automated R script validation. Code review for R scripts checking reproducibility, correctness, and conventions
How do I install review-r?
Run the command: npx killer-skills add naj2r/claude-econ-paper-template/review-r. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.
What are the use cases for review-r?
Key use cases include: Validating R script reproducibility for research papers, Debugging QMD chapters for empirical economics studies, Automating code reviews for data loading and library calls.
Which IDEs are compatible with review-r?
This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.
Are there any limitations for review-r?
Requires access to .R or .qmd files. Limited to R scripts and QMD chapters. Does not support web scraping without caching.
↓ How To Install
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1. Open your terminal
Open the terminal or command line in your project directory.
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2. Run the install command
Run: npx killer-skills add naj2r/claude-econ-paper-template/review-r. The CLI will automatically detect your IDE or AI agent and configure the skill.
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3. Start using the skill
The skill is now active. Your AI agent can use review-r immediately in the current project.
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
review-r
Install review-r, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.