GRIND-Lab-Core
GitHub profile for GRIND-Lab-Core34 skills
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GRIND-Lab-Core / experiment-design
Transforms GIScience proposals into detailed experiment roadmaps, ensuring robust validation and evidence for research claims.
GRIND-Lab-Core / generate-idea
Generates and ranks research ideas based on user-defined directions, facilitating the exploration of publishable research topics.
GRIND-Lab-Core / research-review
Facilitates in-depth critical reviews of research ideas using GPT via Codex MCP, enhancing the quality of research feedback.
GRIND-Lab-Core / paper-draft
Transforms research plans into journal-quality Markdown manuscripts for GIScience and GeoAI, ensuring evidence-based drafting.
GRIND-Lab-Core / data-download
This skill helps users discover, evaluate, and download datasets from the internet, ensuring data integrity and provenance.
GRIND-Lab-Core / experiment-design-pipeline
Facilitates an end-to-end workflow for refining research and designing experiments, producing comprehensive proposals and roadmaps.
GRIND-Lab-Core / paper-figure-generate
Generates high-quality figures and diagrams for GIScience and GeoAI publications, ensuring reproducibility and adherence to journal standards.
GRIND-Lab-Core / paper-review-loop
Enhances academic manuscript drafts through critical review and revision, ensuring alignment with journal standards and improving overall quality.
GRIND-Lab-Core / paper-writing-pipeline
Automates the complete paper writing process from planning to submission-ready manuscript, enhancing research efficiency.
GRIND-Lab-Core / spatial-analysis
Provides a guideline-driven framework for conducting spatial analysis, adapting methods based on research questions and data context.
GRIND-Lab-Core / deploy-experiment
Facilitates deployment and execution of ML/DL and GIScience experiments, managing outputs and logs for analysis.
GRIND-Lab-Core / research-refine
Transforms vague research directions into focused, actionable plans through iterative refinement using GPT-5.4.
GRIND-Lab-Core / training-check
Monitors spatial experiments, categorizing results and firing alerts to ensure efficient research pipeline management.
GRIND-Lab-Core / full-pipeline
Facilitates a comprehensive research pipeline, automating idea discovery, experimentation, review, and reporting for efficient research management.
GRIND-Lab-Core / generate-report
Consolidates research inputs into a comprehensive narrative report to streamline the paper-writing pipeline.
GRIND-Lab-Core / idea-discovery-pipeline
Automates the idea generation process by evaluating research gaps and producing validated research proposals and experiment plans.
GRIND-Lab-Core / novelty-check
Validates research ideas for novelty by searching existing literature and generating a structured novelty report.
GRIND-Lab-Core / paper-covert
Transforms Markdown manuscripts into submission packages, generating LaTeX, PDF, and Word formats based on venue specifications.
GRIND-Lab-Core / submit-check
Validates manuscripts against journal requirements, ensuring compliance with structure, content, and geo-specific standards before submission.
GRIND-Lab-Core / auto-review-loop
Facilitates iterative adversarial reviews to enhance research quality through structured feedback and evaluation cycles.