skills.rest
feast-devfeast-devOfficial·4 Agent Skills Included

feast

Manage and serve machine learning features for training and real-time prediction

Manages machine learning features consistently across model training and real-time serving. Prevents data leakage with point-in-time correct datasets and removes manual dataset joining work. Connects to stores like BigQuery, Snowflake, Redis, and DynamoDB, and supports vector search for RAG pipelines. Includes skills for feature definitions, CLI usage, architecture internals, and testing workflows.
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npx skills add feast-dev/feast --all -g -y
Available:

Tells the AI agent what Feast is, which development commands to run, and how to route tasks to the four bundled skills for user guidance, development, architecture, and testing.

All Skills in This Repository (4)

Pure Emerald Level Indicators
📦 In Repo
feast-devfeast-dev

feast-user-guide

Automate Feast feature management and retrieval workflows with CLI operations.

Official
Intermediate
📦 In Repo
feast-devfeast-dev

feast-dev

Guide Feast contributors through environment setup, testing, and PR workflows.

Official
Intermediate
📦 In Repo
feast-devfeast-dev

feast-architecture

Explains Feast codebase internals, component architecture, and data flows for feature store development.

Official
Intermediate
📦 In Repo
feast-devfeast-dev

feast-testing

Test and debug Feast feature stores with targeted pytest runs and registry inspection.

Official
Intermediate

Frequently Asked Questions

FAQPage Schema
How to install Feast skills?▼

Run `npx skills add feast-dev/feast --all -g -y` in your terminal to install all skills in this suite globally.

What is a feature store used for?▼

A feature store keeps machine learning features consistent between model training and real-time serving, so teams avoid data leakage and duplicated pipeline work.

How do I define and retrieve features with Feast?▼

The feast-user-guide skill shows your agent how to define entities, feature views, and services, then retrieve features online or build point-in-time training datasets.

Can Feast power RAG and vector search?▼

Yes. Feast supports vector-indexed feature views, letting your agent store embeddings and retrieve similar documents for RAG pipelines.

Do these skills work with Claude Code and Codex?▼

Yes. All skills follow the universal SKILL.md standard and work with Claude Code, OpenAI Codex, and other compatible agent tools.

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