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GitHub 저장소

CausalPy

CausalPy에는 pymc-labs에서 수집한 skills 11개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.

수집된 skills
11
Stars
1.2k
업데이트
2026-07-22
Forks
112
직업 범위
직업 카테고리 3개 · 100% 분류됨
저장소 탐색

이 저장소의 skills

review-pr
소프트웨어 품질 보증 분석가·테스터

Review CausalPy pull requests end-to-end by classifying PR type, checking branch freshness, mergeability, remote CI, correctness, security, tests, docs, and maintainer concerns. Use when asked to review a PR, assess a branch before merge, summarize PR risks, or request changes.

2026-07-22
pr-workflows
소프트웨어 개발자

Turn issues into PRs, handle commits, and run prek checks consistently.

2026-07-22
github-issues
소프트웨어 개발자

Create, evaluate, and triage GitHub issues for CausalPy. Use when filing a bug, proposing an enhancement, analyzing existing issues, or splitting large work into parent-child sub-issues.

2026-06-10
pr-to-green
소프트웨어 개발자

Bring a pull request to green by syncing with main, resolving conflicts safely, and fixing failing checks with CausalPy conventions.

2026-06-10
choosing-causalpy-methods
데이터 과학자

Choose the appropriate CausalPy experiment class from a causal or impact question, data structure, treatment assignment, and identification assumptions. Use before writing analysis code when the method is not yet settled, including plain-English questions about whether a campaign, policy, or intervention worked.

2026-06-10
feature-exploration
소프트웨어 개발자

Explore unfamiliar APIs, libraries, or implementation behavior with minimal reproducible examples and documented findings. Use when implementation details are unclear and can be resolved by reading docs, inspecting code, and running focused experiments.

2026-06-08
python-environment
소프트웨어 개발자

Detect, configure, and use a conda-compatible tool. Use before tasks that need the project environment, such as importing project code, running tests, building docs, or invoking repo tooling.

2026-06-08
research-and-planning
소프트웨어 개발자

Perform structured research and turn findings into an implementation plan.

2026-06-08
working-with-marimo
소프트웨어 개발자

Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.

2026-06-08
causal-detective
데이터 과학자

Challenge causal claims through structured threat assessment, counterfactual reasoning, and CausalPy falsification checks. Use when validating whether a causal effect is real or when the user asks "is this effect real?" or "can I trust this result?"

2026-06-08
example-datasets
데이터 과학자

Load built-in CausalPy example datasets for demos, tutorials, tests, and quick causal-analysis prototypes. Use when the user needs sample data or asks which demo datasets are available.

2026-06-08