Skip to main content

pymc-labs/CausalPy

SkillsMP 已收集 pymc-labs/CausalPy 中的 11 个 Skill。打开任一 Skill 可查看来源和详情。

最近记录的来源活动
SkillsMP 收录数据更新
已收集 skills
11
GitHub 星标
1,187
GitHub Forks
114

这个仓库中的 skills

已展示 11 / 11 个已收集 Skill。

职业分类
软件质量保证分析师与测试员
描述

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,…

原文语言:英语

更新
职业分类
软件开发工程师
描述

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

原文语言:英语

更新
职业分类
软件开发工程师
描述

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.

原文语言:英语

更新
职业分类
软件开发工程师
描述

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

原文语言:英语

更新
职业分类
数据科学家
描述

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…

原文语言:英语

更新
职业分类
软件开发工程师
描述

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.

原文语言:英语

更新
职业分类
软件开发工程师
描述

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.

原文语言:英语

更新
职业分类
软件开发工程师
描述

Perform structured research and turn findings into an implementation plan.

原文语言:英语

更新
职业分类
软件开发工程师
描述

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

原文语言:英语

更新
职业分类
数据科学家
描述

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?"

原文语言:英语

更新
职业分类
数据科学家
描述

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.

原文语言:英语

更新
已展示 11 / 11 个已收集 Skill。