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GitHub 저장소

bot-showalter

bot-showalter에는 edpaget에서 수집한 skills 10개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.

수집된 skills
10
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0
업데이트
2026-03-22
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0
직업 범위
직업 카테고리 4개 · 100% 분류됨
저장소 탐색

이 저장소의 skills

rdm-document
소프트웨어 개발자

Generate user documentation from a completed rdm roadmap

2026-03-22
rdm-implement
소프트웨어 개발자

Implement the next phase of an rdm roadmap

2026-03-22
rdm-review
소프트웨어 품질 보증 분석가·테스터

Review implementation of an rdm phase or task

2026-03-22
rdm-roadmap
소프트웨어 개발자

Create an rdm roadmap with phases for a topic

2026-03-22
rdm-tasks
프로젝트 관리 전문가

Work on rdm tasks

2026-03-22
fbm
소프트웨어 개발자

Run fantasy baseball projection commands — predict, evaluate, compare systems, look up player projections/valuations, manage cached datasets, evaluate keeper league trades and optimization, run draft boards and mock drafts, and use Yahoo Fantasy integration for rosters, draft tracking, and keeper cost derivation. Use this when the user asks to run projections, compare systems, evaluate accuracy, look up a player, check valuations, manage/rebuild cached datasets, evaluate keeper league decisions/trades/optimization, view draft boards, run mock drafts, sync Yahoo league data, or manage Yahoo-derived keeper costs.

2026-03-11
experiment-breakout-bust
데이터 과학자

Run an autonomous feature-engineering experiment loop on the breakout-bust classification model. Tests candidate features against P(breakout) and P(bust) probability targets using marginal-value with auto-logging. Use when the user asks to "experiment on breakout-bust", "improve breakout-bust", or "explore features for breakout".

2026-03-06
experiment-playing-time
데이터 과학자

Run an autonomous feature-engineering experiment loop on the playing-time regression model. Tests candidate features against PA (batters) and IP (pitchers) targets using marginal-value with auto-logging. Use when the user asks to "experiment on playing-time", "improve playing-time", or "explore features for playing time".

2026-03-06
experiment
데이터 과학자

Run an autonomous feature-engineering experiment loop on the statcast-gbm model (default). Analyzes residuals, generates feature hypotheses, screens via correlation, tests with fast feedback tools, logs results to the experiment journal, and validates winners. Use when the user asks to "experiment on", "explore features for", or "improve" the statcast-gbm model, or says "experiment on batter/pitcher" without specifying a model. Do NOT use for breakout-bust or playing-time — those have dedicated skills.

2026-03-06
review
소프트웨어 품질 보증 분석가·테스터

Review recent changes against the architectural principles in docs/principles.md. Flags semantic violations that static analysis cannot catch. Use when you want to check a commit, diff, or set of changes for principle violations.

2026-02-28