Automate deterministic data transformation pipelines for gem5 output.
npx skills add https://github.com/nikiitin/RING-5 --skill shaper-pipeline
Please help me install this Agent Skill. Skill: shaper-pipeline Source: https://github.com/nikiitin/RING-5/tree/main/.agent/skills/shaper-pipeline Command: npx skills add https://github.com/nikiitin/RING-5 --skill shaper-pipeline
This Skill helps data teams create and apply deterministic, composable shapers and pipelines to transform gem5 data for analysis and visualization.
Define a pipeline as a list of shaper configurations and apply it to your data using a factory-based runner. Load your data, run the shaper pipeline, and obtain a transformed DataFrame ready for plotting or export.
High-intent search queries and answers about installing and using this skill.
Transform raw gem5 statistics into plot-ready data by defining a configuration list of atomic pandas shapers, which are then instantiated and executed through a factory-based runner to return a clean DataFrame.
A deterministic data transformation pipeline for gem5 output is a composable chain of atomic shapers—such as rename, filter, and normalize—that reliably processes CSV-like statistics across multiple configurations into a structured DataFrame.
Chain data cleaning steps for immutable DataFrame transformations by registering focused, atomic shapers in a factory and composing them into a pipeline via a simple configuration, ensuring each shaper returns a new DataFrame.
You can normalize and aggregate CSV-like statistics across different gem5 configurations by applying specific atomic shapers within your pipeline, which process the raw data into a consistent, analysis-ready format.
No external dependencies are required to use the shaper pipeline framework, as it relies solely on its internal Python data-shaping framework and built-in pandas operations to construct and apply the transformation pipelines.
Use atomic shapers instead of custom data cleaning scripts when you need deterministic, reusable, and composable transformations for gem5 data, allowing you to chain small focused steps rather than maintaining monolithic scripts.
zrt-ai-labLoad CSV files into pandas DataFrames and generate statistical summaries with visualizations.
kongaharshaGenerate publication-quality static and interactive charts from data.
Axel-DaMageAutomate pandas DataFrame operations for cleaning, aggregation, and time series analysis.
Phife726Analyze datasets with SQL, pandas, and statistical methods.
