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dylantmoore/stata-skill
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A skill your agent uses when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices…
Install Aeja Robustness
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustness --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .claude/skills/aeja-robustness && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .claude/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustnessType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustness --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .agents/skills/aeja-robustness && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .agents/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustness --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .cursor/skills/aeja-robustness && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .cursor/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path AEJ-Applied-Economics-Skills/skills/aeja-robustness--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustness --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .gemini/skills/aeja-robustness && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .gemini/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustnessInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .github/skills/aeja-robustness && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .github/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeja-robustness --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/AEJ-Applied-Economics-Skills/skills/aeja-robustness .opencode/skills/aeja-robustness && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aeja-robustness" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/AEJ-Applied-Economics-Skills/skills/aeja-robustness into .opencode/skills/aeja-robustness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeja-robustness", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
aeja-robustness- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 756 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices…
- Works in 5 steps: Lock the primary specification first.… → One threat → one check. A robustness… → Show stability, not just significance.… → …
- An American Economic Journal: Applied Economics (AEJ: Applied) manuscripts headline estimate must be shown to survive specification
- SKILL.md covers When to trigger, The AEJ: Applied robustness bar, Robustness craft and Execution bridge (StatsPAI /…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Aeja Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices before submission or in an R&R. Builds the robustness suite a sophisticated referee expects; it does not establish the primary identification (aeja-identification) or format the exhibits (aeja-tables-figures).
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Econometrics and empirical research. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- An American Economic Journal: Applied Economics (AEJ: Applied) manuscripts headline estimate must be shown to survive specification
- Inference choices before submission
Example prompts
- “/aeja-robustness”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Lock the primary specification first. Everything else is a perturbation around it; do not present five co-equal specs and let the reader…
- One threat → one check. A robustness table should read as "here is the worry, here is the evidence it is not a problem."
- Show stability, not just significance. The persuasive object is that the point estimate barely moves, not that it stays starred.
- Be honest about where it weakens. A check that shifts the estimate is information; report it and bound the implication rather than hiding…
- Match inference to the data structure (clustering, spatial dependence, few clusters) — wrong SEs are the most common AEJ: Applied…
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Aeja Robustness loads about 1.7k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 756 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 756 words, ~1,679 tokens.
Download SKILL.mdSave it as
.claude/skills/aeja-robustness/SKILL.md (or your agent's skills folder).- name
- aeja-robustness
- description
- Use when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices before submission or in an R&R. Builds the robustness suite a sophisticated referee expects; it does not establish the primary identification (aeja-identification) or format the exhibits (aeja-tables-figures).
Robustness Suite (aeja-robustness)
When to trigger
- The main estimate is in hand and you need to show it is not an artifact of one specification
- A referee asks "is this robust to [alternative controls / sample / functional form / inference]?"
- The result depends on a bandwidth, a clustering choice, or a sample-selection rule that could be questioned
- You suspect specification-search concerns and want to pre-empt them
The AEJ: Applied robustness bar
AEJ: Applied referees probe whether the headline number is stable, honestly inferred, and not the product of researcher degrees of freedom. Robustness here is not a wall of regressions — it is a targeted set of checks each tied to a specific threat to the design. Map every plausible objection to the one check that answers it, and report the checks so the reader sees the estimate barely moves.
| Threat to the result | The check that answers it |
|---|---|
| Omitted confounders | Oster δ / coefficient-stability bounds; added controls in steps |
| Specification search | a specification curve / multiverse; pre-registered primary spec |
| Functional form | levels vs logs, alternative outcome definitions, nonparametric version |
| Sample selection | drop influential units, alternative inclusion rules, balanced vs unbalanced panel |
| Inference too narrow | clustered SEs at the right level, wild-cluster bootstrap (few clusters), randomization inference |
| Design-specific fragility | DID: honest-DID bounds; RD: bandwidth/donut; IV: weak-IV-robust set |
| Multiple outcomes/subgroups | Romano–Wolf / List–Shaikh–Wooldridge MHT adjustment |
Robustness craft
- Lock the primary specification first. Everything else is a perturbation around it; do not present five co-equal specs and let the reader guess which is preferred.
- One threat → one check. A robustness table should read as "here is the worry, here is the evidence it is not a problem."
- Show stability, not just significance. The persuasive object is that the point estimate barely moves, not that it stays starred.
- Be honest about where it weakens. A check that shifts the estimate is information; report it and bound the implication rather than hiding it.
- Match inference to the data structure (clustering, spatial dependence, few clusters) — wrong SEs are the most common AEJ: Applied robustness failure.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. AEJ: Applied is applied microeconomics — labor, health, education, and development field settings where a clean research design is the entry ticket.
- Many outcomes / specifications:
romano_wolf(step-down FWER, accounts for cross-test correlation) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr— the confounder strength that would overturn the headline. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each — no guessing the battery. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Keep the decisive checks in the body and the exhaustive (now actually-run) battery in the appendix. See the executed chain in the JF execution walkthrough.
Show full SKILL.md (294 more words)Show less
Checklist
- Primary specification declared (ideally pre-registered) before perturbations
- Each robustness check mapped to a specific threat, not added for volume
- Coefficient-stability evidence (Oster δ or stepwise controls) for selection-on-unobservables
- Inference stress-tested: correct clustering level + wild-cluster/randomization inference where relevant
- Design-specific sensitivity included (honest-DID / RD bandwidth / weak-IV set)
- Multiple-hypothesis adjustment if many outcomes/subgroups
- Stability of the point estimate shown, and any check that moves it reported honestly
Anti-patterns
- A 20-column robustness table with no map from check to threat ("kitchen-sink robustness")
- Reporting only that significance survives while the point estimate wanders
- Hiding the specification that breaks the result
- Clustering at the wrong level or ignoring few-cluster bias, then claiming robustness
- Treating "added more controls and it survived" as sufficient for selection on unobservables
- Subgroup p-hacking with no MHT correction
Worked vignette (illustrative)
An IV estimate of the return to a training program is 0.11 (s.e. 0.04). The robustness suite: (i) effective F of 23 rules out weak instruments; (ii) the Anderson–Rubin 95% set is [0.04, 0.19], so inference is not weak-IV-fragile; (iii) Oster δ implies selection on unobservables would need to be 1.8× selection on observables to nullify it; (iv) wild-cluster bootstrap with 14 clusters keeps the CI away from zero; (v) dropping the largest region moves the estimate to 0.10. The point estimate barely moves — the AEJ: Applied target.
Referee pushback mapped to the robustness fix
- "This looks like specification search." → Declare the pre-registered or primary spec; show a specification curve in which the point estimate barely moves.
- "Did you cluster correctly?" → Cluster at the assignment level; with few clusters report a wild-cluster bootstrap or randomization-inference p-value.
- "Could selection on unobservables explain this?" → Report Oster δ; state how strong selection on unobservables would have to be (relative to observables) to nullify the result.
Output format
【Primary spec】declared / pre-registered? [Y/N] — estimate: ___ (s.e. ___)
【Threat → check map】selection: ___ | spec-search: ___ | form: ___ | sample: ___ | inference: ___ | design: ___
【Inference】clustering level: ___; few-cluster/randomization: ___
【Design sensitivity】honest-DID / RD bandwidth / weak-IV set: ___
【Estimate stability】range across checks: [___, ___]; checks that move it: ___
【Next step】aeja-tables-figures© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in AEJ-Applied-Economics-Skills/skills/aeja-robustness of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Aeja Robustness next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Aeja Robustness this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Statadylantmoore/stata-skill | 291 | 1 repos | ~4.2k | Automated safety check: Pass | Custom licence | |
| Stata C Pluginsdylantmoore/stata-skill | 291 | 1 repos | ~5.8k | Automated safety check: Pass | Custom licence | |
| Example Datasetspymc-labs/CausalPy | 1.2k | — | ~587 | Automated safety check: Pass | Apache-2.0 | |
| Stata AuditSepineTam/mcp-for-stata | 264 | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | |
| Stata Skill Contributordylantmoore/stata-skill | 291 | 1 repos | ~2.4k | Automated safety check: Pass | Custom licence |
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Questions about Aeja Robustness
What does Aeja Robustness do?
A skill your agent uses when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices…. Aeja Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices before submission or in an R&R.
When should I use Aeja Robustness?
Aeja Robustness fits situations like: an American Economic Journal: Applied Economics (AEJ: Applied) manuscripts headline estimate must be shown to survive specification; inference choices before submission.
How do I install Aeja Robustness in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a claude-code`. Or copy the skill folder (AEJ-Applied-Economics-Skills/skills/aeja-robustness in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/aeja-robustness in your project. Claude Code loads it when a task matches its description.
How do I install Aeja Robustness in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a codex`. Or copy the skill folder (AEJ-Applied-Economics-Skills/skills/aeja-robustness in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/aeja-robustness in your project. Codex loads it when a task matches its description.
Can I use Aeja Robustness in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aeja-robustness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aeja-robustness, .gemini/skills/aeja-robustness, .github/skills/aeja-robustness and .opencode/skills/aeja-robustness in your project.
What does Aeja Robustness need to run?
SKILL.md names no scripts, command-line tools or credentials: Aeja Robustness is instructions for the agent only.
Does Aeja Robustness access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Aeja Robustness safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Aeja Robustness use?
Aeja Robustness is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Aeja Robustness use?
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Aeja Robustness?
Skills that share tags, products or a category with Aeja Robustness: Stata (dylantmoore/stata-skill, 291 stars), Stata C Plugins (dylantmoore/stata-skill, 291 stars), Example Datasets (pymc-labs/CausalPy, 1.2k stars) and Stata Audit (SepineTam/mcp-for-stata, 264 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Aeja Robustness?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.