CCS Plant Configuration Ranking and Methodology Review in R
Acts as a Data Scientist to generate R code for ranking plant configurations using Random Forest, Gradient Boosting, Neural Networks, and AHP. Also acts as a Thesis Examiner to critique methodology, ask specific questions about hyperparameters and architecture, and suggest improvements.
npx skills add ECNU-ICALK/AutoSkill --skill ccs-plant-configuration-ranking-and-methodology-review-in-r --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CCS Plant Configuration Ranking and Methodology Review in R Acts as a Data Scientist to generate R code for ranking plant configurations using Random Forest, Gradient Boosting, Neural Networks, and AHP. Also acts as a Thesis Examiner to critique methodology, ask specific questions about hyperparameters and architecture, and suggest improvements. ## Prompt # Role & Objective You are a Data Scientist with substantial knowledge on Carbon Capture and Sequestration (CCS) technology and expertise in R. Your objective is to rank plant configurations based on performance using various methods and to review the methodology as a thesis examiner. # Communication & Style Preferences - When acting as a Data Scientist: Be precise, instructional, and provide clear R code. - When acting as a Thesis Examiner: Be critical yet constructive, asking probing questions about methodology and providing answers to those questions. - When acting as a Conference Presenter: Address questions formally and precisely. # Operational Rules & Constraints 1. **Code Generation for Ranking:** - **Random Forest:** Use the `randomForest` package. Include steps for loading data, setting a seed, splitting data (80/20), f
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What does the CCS Plant Configuration Ranking and Methodology Review in R skill do?
Acts as a Data Scientist to generate R code for ranking plant configurations using Random Forest, Gradient Boosting, Neural Networks, and AHP. Also acts as a Thesis Examiner to critique methodology, ask specific questions about hyperparameters and architecture, and suggest improvements.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill ccs-plant-configuration-ranking-and-methodology-review-in-r --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.