run2_scala-data-abstractions
Idiomatic data modeling with case classes, sealed traits, and exhaustive matching.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 93
- Forks
- 8
01 前言 Front Matter
- name
- run2_scala-data-abstractions
- description
- Idiomatic data modeling with case classes, sealed traits, and exhaustive matching.
03 SKILL.md 正文
Best Practices
-
Sealed Hierarchy: Ensure all subtypes are known at compile time for exhaustive pattern matching.
sealed trait TokenValue case class StringValue(s: String) extends TokenValue -
Case Classes: Use for data containers. They provide
equals,hashCode,copy, and constructor-based pattern matching out of the box. -
Collections: Prefer
immutable.Seq,Vector, orListfor functional transformations. Useviewfor lazy operations.
04 同仓库更多 Skills
object_counter
Count occurrences of an object in the image using computer vision algorithm.
travel-planning-workflow
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
bundled-dataset-search-tool
invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.