Skills

Full-empirical-analysis-skill-Stata

Full-empirical-analysis-skill-Stata is a skill in brycewang-stanford/Auto-Empirical-Research-Skills, last changed 2 Sept 2026. It can run shell commands and name web addresses. Our pattern check found 1 item to review at commit 371a40e on 27 Oct 2026.

Pattern check: 1 item to review · commit 371a40e · 27 Oct 2026

Install
From the author
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `teffects ipw` / `teffects ipwra` / `teffects aipw` / `eltmle`, Mendelian randomization via `mrrobust` (IVW / Egger / weighted median) and `mregger` / `mrpresso`, KM / Cox / AFT / RMST survival via `sts` / `stcox` / `streg` / `strmst2`, E-value sensitivity via `evalue` (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `ddml` / `pdslasso`, S/T/X/R/DR meta-learners via `crforest` and `ddml interactive`, causal forest via `crforest` / `cforest`, BART/BCF via `bart` / `bartCause`-style externals, CATE distribution + policy tree via `crforest`, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via `pcalg` / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
Licence
Licence not identified
Repo stars
4.8k
Folder last changed
2 Sept 2026 (opens in a new tab)
Publisher
brycewang-stanford
Files
9 files
Checked
371a40e (opens in a new tab) · 27 Oct 2026

Install

Each tab says whether it installs commit 371a40e, the one we checked, or the latest version.

No tab for your agent? Use Any agent for OpenCode, Goose, Windsurf (Devin Desktop), Zed, Roo Code, Factory Droid, Junie, Amp and Antigravity, and Claude Code for Cline. Kiro needs the folder copied by hand.

Pinned to commit 371a40e, the one we checked.

From your project's root folder:

tmp="$(mktemp -d)" &&
  git clone -q --depth 1 --filter=blob:none --no-checkout https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git "$tmp" &&
  git -C "$tmp" fetch -q --depth 1 origin 371a40e488c5d9e8e75ca2af5dd9667f8349c199 &&
  git -C "$tmp" sparse-checkout set -- plugins/empirical-analysis-stata/skills/pipeline &&
  git -C "$tmp" checkout -q 371a40e488c5d9e8e75ca2af5dd9667f8349c199 &&
  mkdir -p .claude/skills &&
  mkdir .claude/skills/pipeline &&
  cp -R "$tmp"/plugins/empirical-analysis-stata/skills/pipeline/. .claude/skills/pipeline/ &&
  rm -rf "$tmp"

If Claude Code was already running and this created the skills folder, run /reload-skills.

Or install the empirical-analysis-stata plugin it ships in. Installs the latest version, not the one we checked. Installs everything in the plugin, including any hooks, MCP servers and scripts our check doesn't cover.

claude plugin marketplace add brycewang-stanford/Auto-Empirical-Research-Skills --scope project &&
  claude plugin install empirical-analysis-stata@auto-empirical-research-skills --scope project
Claude Code docs (opens in a new tab)

What it can touch

From the files and frontmatter at commit 371a40e. This is how much a skill can do, not whether it is risky.

What it can touch: Scripts or outside hosts

  • Runs shell commands

    Its instructions or files give the agent commands to run on your computer.

  • Names web addresses

    It mentions outside web addresses the agent may visit. We list them but don't follow them.

Pattern check

Pattern check: 1 item to review · commit 371a40e · 27 Oct 2026

We checked every text file in this skill, at commit 371a40e on 27 Oct 2026, against 45 published patterns such as download-and-run commands, hidden text and credential access. We don't run the skill, we don't read the web pages it points to, and we can't judge everything its instructions might lead an agent to do. In published tests, pattern checks like this one missed most malicious skills. Read the skill before you install it — especially anything it asks you to download or run.

How the check worksReport an incorrect finding

Outside links we did not follow

  • https://stats.idre.ucla.edu/stat/stata/examples/chp4/crime

Format check

Each agent reads SKILL.md a little differently. We check the file against each one's published rules; we don't run the skill in any agent.

  • Agent Skills specFails

    The open format from agentskills.io, held to what the strictest agents enforce, so one folder loads everywhere.

    • Error

      The name "Full-empirical-analysis-skill-Stata" has uppercase letters. Names may use only a–z, 0–9 and single hyphens. N3

      Fix: Use name: full-empirical-analysis-skill-stata and rename the folder to match.

    • Error

      The name "Full-empirical-analysis-skill-Stata" doesn't match its folder "pipeline". The spec requires them to match. N4

      Fix: Set name: pipeline, or rename the folder to full-empirical-analysis-skill-stata.

    • Error

      The description is 3,185 characters; the limit is 1,024. D2

      Fix: Shorten it to 1,024 characters or fewer, and move detail into the body.

    • Warning

      Fields outside the spec: triggers. Uploads to the Claude apps and API, and the spec's validator, reject the file; most agents ignore these fields. O1

      Fix: Delete them for a portable skill, or keep them if you only target the agents that read them.

    • Warning

      The body is 2334 lines; the spec suggests under 500. B1

      Fix: Move detailed sections into reference files and link to them from SKILL.md.

    • Warning

      The body is about 29,858 tokens (approx.); the spec suggests under 5,000. B2

      Fix: Move detail into reference files that the agent reads only when needed.

    • Note

      The first sentence of the description is 291 characters. Agents shorten long descriptions, so lead with the main job. D8

      Fix: Start with one short sentence that names the job.

    • Note

      There is no license field, so readers can't tell whether they may reuse the skill. O2

      Fix: Add license: with an SPDX name such as MIT or Apache-2.0, or the name of a bundled licence file.

  • Claude CodePasses with warnings

    Claude Code reads its own extra fields, ignores unknown ones, and still loads a skill whose frontmatter is broken, without its fields.

    • Warning

      The description comes to 3,185 characters; Claude Code's skill listing cuts each entry at 1,536. The listing keeps every skill's name, but past its budget (1% of the context window) Claude Code drops descriptions, starting with the skills used least. D5

      Fix: Put the key use case first, or move detail into the body.

    • Note

      The name "Full-empirical-analysis-skill-Stata" doesn't match its folder "pipeline". Claude Code shows the skill as /Full-empirical-analysis-skill-Stata, and the folder name also invokes it. N4

      Fix: Set name: pipeline, or rename the folder to full-empirical-analysis-skill-stata.

    • Note

      The first sentence of the description is 291 characters. Agents shorten long descriptions, so lead with the main job. D8

      Fix: Start with one short sentence that names the job.

    • Note

      Claude Code ignores fields it doesn't know: triggers. O1

      Fix: Check the spelling against Claude Code's field list, or delete them.

    • Note

      The body is 2334 lines; the spec suggests under 500. Claude Code's docs say the same. B1

      Fix: Move detailed sections into reference files and link to them from SKILL.md.

    • Note

      The body is about 29,858 tokens (approx.); the spec suggests under 5,000. After compaction Claude Code keeps only the first 5,000 tokens of a skill. B2

      Fix: Move detail into reference files that the agent reads only when needed.

  • Claude apps & API uploadFails

    Uploading to claude.ai or the Claude API, or packaging with Anthropic's script, accepts only the six spec fields and stops on anything else.

    • Error

      The name "Full-empirical-analysis-skill-Stata" has uppercase letters. Anthropic's validator allows only lowercase letters, digits and hyphens. N3

      Fix: Use name: full-empirical-analysis-skill-stata and rename the folder to match.

    • Error

      The name "Full-empirical-analysis-skill-Stata" doesn't match its folder "pipeline". claude.ai refuses an upload whose folder name doesn't match the skill name. N4

      Fix: Set name: pipeline, or rename the folder to full-empirical-analysis-skill-stata.

    • Error

      The description is 3,185 characters; the limit is 1,024. Anthropic's validator rejects it. D2

      Fix: Shorten it to 1,024 characters or fewer, and move detail into the body.

    • Error

      Upload and packaging fail on fields outside the spec: triggers. O1

      Fix: Delete them, and keep your own data under metadata as text values.

    • Note

      The body is 2334 lines; the spec suggests under 500. Anthropic's guidance says the same. B1

      Fix: Move detailed sections into reference files and link to them from SKILL.md.

    • Note

      The body is about 29,858 tokens (approx.); the spec suggests under 5,000. Anthropic's guidance says the same. B2

      Fix: Move detail into reference files that the agent reads only when needed.

  • OpenAI (Codex & API)Fails

    Codex finds SKILL.md by its exact name and needs a description; OpenAI's Skills API checks the frontmatter against the spec and caps uploads.

    • Error

      The name "Full-empirical-analysis-skill-Stata" has uppercase letters. OpenAI's upload follows the spec, which allows only a–z, 0–9 and hyphens. N3

      Fix: Use name: full-empirical-analysis-skill-stata and rename the folder to match.

    • Error

      The description is 3,185 characters; the limit is 1,024. Codex has no limit, but OpenAI's upload follows the spec. D2

      Fix: Shorten it to 1,024 characters or fewer, and move detail into the body.

    • Warning

      The name "Full-empirical-analysis-skill-Stata" doesn't match its folder "pipeline". OpenAI's own upload example uses a differently named folder, but the spec it follows says they must match. N4

      Fix: Set name: pipeline, or rename the folder to full-empirical-analysis-skill-stata.

    • Warning

      Fields outside the spec: triggers. Codex ignores them; OpenAI doesn't say whether its upload accepts them. O1

      Fix: Delete them, or move your own data under metadata as text values.

    • Note

      The first sentence of the description is 291 characters. Agents shorten long descriptions, so lead with the main job. D8

      Fix: Start with one short sentence that names the job.

  • VS Code & CopilotPasses with warnings

    VS Code reads skills one folder below .github/skills, .claude/skills or .agents/skills and falls back to the folder name when the name is missing or differs; GitHub's Copilot docs require the exact name SKILL.md.

    • Warning

      The name "Full-empirical-analysis-skill-Stata" has uppercase letters. VS Code uses the folder name whenever the name differs from it. N3

      Fix: Use name: full-empirical-analysis-skill-stata and rename the folder to match.

    • Warning

      The name "Full-empirical-analysis-skill-Stata" doesn't match its folder "pipeline". VS Code uses the folder name, pipeline, instead. N4

      Fix: Set name: pipeline, or rename the folder to full-empirical-analysis-skill-stata.

    • Warning

      The description is 3,185 characters; the limit is 1,024. VS Code cuts it at 1,024 characters. D2

      Fix: Shorten it to 1,024 characters or fewer, and move detail into the body.

    • Note

      VS Code ignores fields it doesn't support: triggers. O1

      Fix: Delete them unless another agent you target reads them.

SKILL.md

We only show SKILL.md text here when its licence clearly allows it.

Read SKILL.md on GitHub (opens in a new tab)

Files

9 files

PathSize
SKILL.md (opens in a new tab)123 KB
references/01-data-cleaning.md (opens in a new tab)12.6 KB
references/02-data-transformation.md (opens in a new tab)11 KB
references/03-descriptive-stats.md (opens in a new tab)10.5 KB
references/04-statistical-tests.md (opens in a new tab)10.5 KB
references/05-modeling.md (opens in a new tab)19.7 KB
references/06-robustness.md (opens in a new tab)12.6 KB
references/07-further-analysis.md (opens in a new tab)12.6 KB
references/08-tables-plots.md (opens in a new tab)15.5 KB

Copies

These share its SKILL.md or its name and description but not all its files, so we list them separately.

More from brycewang-stanford/Auto-Empirical-Research-Skills

  • a1

    brycewang-stanford/Auto-Empirical-Research-Skills

    VS-Enhanced Research Question Refiner - Prevents Mode Collapse and derives differentiated research questions Enhanced VS 3-Phase process: Modal question avoidance, alternatives presentation, differentiated RQ recommendation Use when: refining research ideas, formulating research questions, clarifying scope Triggers: research question, 연구 질문, PICO, SPIDER, research idea

    • Instructions only
    Pattern check: Nothing flagged

    No licence · 4.8k repo stars · Updated 2 Apr 2026

  • a2

    brycewang-stanford/Auto-Empirical-Research-Skills

    VS-Enhanced Theoretical Framework Architect with Critique & Visualization Full VS 5-Phase process: Modal theory avoidance, Long-tail exploration, differentiated framework presentation Absorbed A3 (Devil's Advocate) critique and A6 (Conceptual Framework Visualizer) capabilities Use when: building theoretical foundations, designing conceptual models, deriving hypotheses, critiquing frameworks, visualizing models Triggers: theoretical framework, 이론적 프레임워크, conceptual model, 개념적 모형, hypothesis derivation, critique, devil's advocate, 반론, visualization, diagram

    • Instructions only
    Pattern check: Nothing flagged

    No licence · 4.8k repo stars · Updated 2 Apr 2026

  • a5

    brycewang-stanford/Auto-Empirical-Research-Skills

    Agent A5 - Paradigm & Worldview Advisor - Philosophical foundations for research design. Covers ontology, epistemology, axiology, and methodology alignment. Use when: establishing philosophical foundations, justifying methodological choices, writing positionality statements Triggers: paradigm, 패러다임, ontology, epistemology, worldview, 세계관, philosophical foundations, 철학적 기초

    • Instructions only
    Pattern check: Nothing flagged

    No licence · 4.8k repo stars · Updated 2 Apr 2026

  • ablation-planner

    brycewang-stanford/Auto-Empirical-Research-Skills

    Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission. Codex designs ablations from a reviewer's perspective, CC reviews feasibility and implements.

    • Runs shell commands
    • Pre-approves tools
    Pattern check: 1 item to review

    No licence · 4.8k repo stars · Updated 19 Jul 2026

  • ablation-planner

    brycewang-stanford/Auto-Empirical-Research-Skills

    Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.

    • Runs shell commands
    • Pre-approves tools
    Pattern check: 1 item to review

    No licence · 4.8k repo stars · Updated 2 Apr 2026

  • abstract

    brycewang-stanford/Auto-Empirical-Research-Skills

    Reads the manuscript and notebooks to generate a structured abstract. Use when writing or updating the abstract.

    • Runs shell commands
    • Pre-approves tools
    Pattern check: 1 item to review

    No licence · 4.8k repo stars · Updated 2 Apr 2026

All skills in brycewang-stanford/Auto-Empirical-Research-Skills