Robustness Table
- 1 installs
- 3.2k repo stars
- Updated August 4, 2026
- brycewang-stanford/awesome-agent-skills-for-empirical-research
robustness-table is a Claude skill that generates robustness-check code from a baseline regression and formats the results as a combined sensitivity-analysis table.
About
A skill that generates robustness-check code from a baseline regression and formats the results as a combined sensitivity-analysis table. It creates specifications such as alternative controls, alternative fixed effects, different clustering levels, subsample analysis, winsorizing, and placebo tests, then collects them into one publication-ready table. A researcher uses it to add sensitivity analysis to a paper. It recognizes statsmodels, linearmodels, R fixest, and Stata output.
- Generates robustness-check code from a baseline regression
- Combines results into a publication-ready sensitivity-analysis table
- Covers alternative controls, FE, clustering, subsamples, and placebo tests
Robustness Table by the numbers
- 1 all-time installs (skills.sh)
- Ranked #1,803 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
robustness-table capabilities & compatibility
- Capabilities
- robustness table · regression table · sensitivity analysis
- Use cases
- data analysis · documentation
What robustness-table says it does
Generates robustness check code and formats results as a combined table. Use for sensitivity analysis.
Format: baseline in column (1), each robustness check in subsequent columns
Placebo tests (randomized treatment, pre-period outcome)
npx skills add https://github.com/brycewang-stanford/awesome-agent-skills-for-empirical-research --skill robustness-tableAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 1 |
|---|---|
| repo stars | ★ 3.2k |
| Last updated | August 4, 2026 |
| Repository | brycewang-stanford/awesome-agent-skills-for-empirical-research ↗ |
What it does
Generate robustness-check specifications from a baseline regression and format them into a combined table.
Who is it for?
Producing a robustness / sensitivity-analysis table from a baseline regression specification.
Skip if: Running the baseline regression itself, which must already exist in the notebook.
When should I use this skill?
You have a baseline regression and need robustness checks formatted into a combined table.
What you get
Robustness-check code plus a publication-ready combined table with the baseline in column one.
- Robustness-check code cells
- Combined robustness table
- Quarto embed shortcode
Files
Generate Robustness Checks and Table
Given a baseline regression, generate code for standard robustness checks and format the results as a publication-ready table.
Arguments
$ARGUMENTS— notebook reference and baseline specification description (e.g., "notebook-02 baseline OLS with GDP on life expectancy")
Steps
1. Read the specified notebook and locate the baseline regression:
- Look for estimation commands (Python:
statsmodels,linearmodels; R:lm,fixest,felm; Stata:reg,reghdfe,ivregress) - Identify the dependent variable, independent variables, fixed effects, and clustering
2. Ask the user which robustness checks to include:
- Alternative control variable sets (drop/add controls)
- Alternative fixed effects specifications
- Different standard error clustering levels
- Subsample analysis (e.g., by region, time period, income group)
- Winsorized or trimmed dependent variable
- Alternative dependent variable (e.g., log vs level)
- Placebo tests (randomized treatment, pre-period outcome)
- Alternative estimation methods (e.g., OLS vs Poisson, logit vs probit)
3. Generate code cells in the notebook for each robustness specification:
- Each cell should be self-contained (loads data, runs regression, stores results)
- Use consistent variable naming for results collection
4. Create a summary cell that collects all results into a single table:
- Cell directive:
#| label: tbl-robustness(or*|for Stata) - Cell directive:
#| tbl-cap: "Robustness checks"(or*|for Stata) - Format: baseline in column (1), each robustness check in subsequent columns
- Follow academic conventions: coefficient (SE), significance stars, N, R², FE indicators
- Stata caveat: Do NOT use
tbl-prefix for Stata text output — use a plain label (e.g.,stata-robustness)
5. Optionally export the table to tables/ as a standalone file (LaTeX or CSV)
6. Sync the Jupytext pair:
uv run jupytext --sync notebooks/<name>.md7. Show the embed shortcode for index.qmd:
{{< embed notebooks/<name>.ipynb#tbl-robustness >}}Error handling
- If the baseline regression is not found, ask the user to point to the specific cell.
- If the notebook uses a language not recognized, ask for guidance on the estimation syntax.
Related skills
Microsoft FoundryDeploy, evaluate, and continuously improve Microsoft Foundry agents from a single agent interface.490k1.3k
Ai Research ReproductionOrchestrate trustworthy, auditable reproduction of deep learning repositories directly from their READMEs.176k511Run TrainSafely execute selected deep learning training commands with standardized evidence capture.176k511Explore RunSafely run isolated exploratory experiments with clear recording and conservative selection before committing changes.176k511Paper Context ResolverFetch precise reproduction-critical details like dataset splits, preprocessing steps, or evaluation protocols from the original academic paper when the repo README leav141k511Repo Intake And PlanScan unfamiliar AI research repositories and receive a minimal, trustworthy reproduction target before investing significant time.140k511FAQ
What does the robustness-table skill do?
It generates code for standard robustness checks from a baseline regression and formats the combined results into a publication-ready table.
What checks can it include?
Alternative controls and fixed effects, different clustering, subsample analysis, winsorized outcomes, placebo tests, and alternative estimation methods.