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ray-data

An AI agent skill from Orchestra-Research/AI-Research-SKILLs, scored 57 out of 100 by code.

57/ 100C

Code score by group

  • Spec20/20
  • Description11/20
  • Procedure0/15
  • Done criteria0/15
  • Resources9/10
  • Scripts5/8
  • Safety7/7
  • Upkeep5/5

It loses the most points in Procedure (15), the group that checks whether the steps are numbered, read the context first and say what to do when something fails.

What the author says it does

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.

Repository
Orchestra-Research/AI-Research-SKILLs
Folder
05-data-processing/ray-data
License
MIT
GitHub stars
14,480
SKILL.md lines
327
Other files
2

Add ray-data to your agent

npx skills add Orchestra-Research/AI-Research-SKILLs --skill ray-data

The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.

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All skills in Orchestra-Research/AI-Research-SKILLs

Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.