cuDF Analytics Skill
Skill TerverifikasiUse for GPU-accelerated data analysis on datasets, CSVs, or tabular data using NVIDIA cuDF. Triggers when tasks involve groupby aggregations, statistical summaries, anomaly detection, or large-scale data profiling.
This skill leverages NVIDIA cuDF to perform accelerated data analysis on CSVs and tabular data, supporting operations like statistical summaries, groupby aggregations, and anomaly detection. It includes a fallback to pandas for systems without GPU support and provides clear examples for its use.
Documentation
- info:Configuration & parameter referenceParameters like file paths are mentioned, but default values for configurations are not explicitly documented. The initialization code is clear but lacks documentation on potential configuration overrides.
Code Execution
- info:ValidationInput file paths are implicitly validated by the `read_csv` function, but explicit schema validation libraries are not used for input arguments or output structures.
- info:LoggingThe script includes print statements for GPU unavailability and conversion errors, but there is no structured local audit file for actions or outcomes.
Practical Utility
- info:Edge casesThe initialization handles GPU unavailability, and the `to_pd` function has a fallback, but explicit documentation of other failure modes (e.g., malformed CSV, missing columns) and their recovery paths is missing.
Instalasi
npx skills add langchain-ai/deepagentsMenjalankan Vercel skills CLI (skills.sh) via npx — memerlukan Node.js secara lokal dan setidaknya satu agen yang kompatibel dengan skills terinstal (Claude Code, Cursor, Codex, …). Mengasumsikan repo mengikuti format agentskills.io.
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