pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Show current session status and context health for the sewage project. Use to check context usage, active work state, and what will survive compaction.
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill context-status --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/context-statusContext preview
The summary Claude sees to decide when to auto-load this skill.
Show current session status and context health for the sewage project. Use to check context usage, active work state, and what will survive compaction.
name: context-status description: | Show current session status and context health for the sewage project. Use to check context usage, active work state, and what will survive compaction. allowed-tools: ["Bash", "Read", "Glob"]
Show current session status including context usage estimate and project state.
# Recent git activity git log --oneline -5 # Working tree status git status --short # Recent output files ls -lt output/log/ 2>/dev/null | head -5
# Count analysis scripts find scripts/R/09_analysis/ -name "*.R" | wc -l # Count output tables and figures ls output/tables/*.tex 2>/dev/null | wc -l ls output/figures/ 2>/dev/null | wc -l # Check manuscript sections ls docs/overleaf/*.tex 2>/dev/null
Format output:
Session Status --- Recent commits: [last 3] Uncommitted changes: [count] Recent reports: [last 3 in output/log/] Project Progress --- Pipeline scripts: N Analysis scripts: N Output tables: N Output figures: N Manuscript sections: N .tex files Memory Files --- [List files in .claude/projects/.../memory/]
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
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Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
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