New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Aejmic Robustness

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions…

MITAuto-check passedResearch & Science

Install Aejmic Robustness

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-robustness -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aejmic-robustness --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/AEJ-Microeconomics-Skills/skills/aejmic-robustness .claude/skills/aejmic-robustness && rm -rf skills-src

Use ~/.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/

Facts

Skill name
aejmic-robustness
GitHub stars
1.2k
Token cost
~1.6k tokens
SKILL.md length
723 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions…

  • Works in 2 steps: Broadens the contribution — the result… → Defends a load-bearing assumption — it…
  • Alternative concepts
  • SKILL.md covers When to trigger, What robustness means at AEJ:…, Execution bridge (StatsPAI /… and Checklist, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Aejmic Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions (relaxed assumptions, alternative concepts, perturbations) and applied/experimental robustness. Decides which extensions earn their place; it does not prove the main result (see aejmic-theory-model).

Its SKILL.md is about 1.6k 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. 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

  • Alternative concepts
  • Perturbations) and applied/experimental robustness

Example prompts

  • “/aejmic-robustness”

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Broadens the contribution — the result now covers a setting readers care about (continuum types, dynamics, asymmetry) that the base model…
  2. Defends a load-bearing assumption — it answers the specific "is this knife-edge?" objection that aejmic-identification flagged.

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

Aejmic Robustness loads about 1.6k tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 723 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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). 723 words, ~1,644 tokens.

Download SKILL.mdSave it as .claude/skills/aejmic-robustness/SKILL.md (or your agent's skills folder).
name
aejmic-robustness
description
Use when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions (relaxed assumptions, alternative concepts, perturbations) and applied/experimental robustness. Decides which extensions earn their place; it does not prove the main result (see aejmic-theory-model).

Robustness, Extensions & Edge Cases (aejmic-robustness)

When to trigger

  • The main result is proved but referees will ask "does it survive [relaxation]?"
  • You have many possible extensions and must decide which belong in the paper
  • A knife-edge or boundary case is unaddressed
  • (Applied) The empirical/experimental result needs a robustness battery

What robustness means at AEJ: Micro

For a theory paper, robustness is about the mechanism's reach: which relaxations preserve the result, which break it, and which boundary cases need care. AEJ: Micro values knowing the edges of a result as much as the result. For structural/experimental work, it is the standard robustness battery. The discipline is the same: every extension must earn its place — it either broadens the contribution or defends a load-bearing assumption flagged in aejmic-identification.

Theory extensions — the menu (include only what earns its place)
  • Relax a substantive assumption: continuum vs. finite types, asymmetric vs. symmetric players, correlated vs. independent values. Show the qualitative result survives or pin down where it changes.
  • Alternative solution concept / refinement: does the result hold under a coarser or finer equilibrium notion? If it is concept-specific, say so.
  • Perturbations: small changes to the information structure, timing, or commitment level (full → partial). Continuity/upper-hemicontinuity arguments belong here.
  • Boundary and knife-edge cases: tie-breaking, measure-zero events, corner solutions — handle explicitly, do not hand-wave.
  • Negative extensions are informative: an extension that fails and explains why sharpens the contribution and pre-empts a referee.
Applied / experimental robustness
  • Alternative specifications/estimators; sensitivity to grids, tuning, and seeds (structural/simulation).
  • Placebo / falsification; multiple-testing adjustment; subsample stability.
  • Report as SEs / coverage sets, never significance asterisks.
The "earns its place" test

Before adding an extension, ask which of two jobs it does. If it does neither, cut it.

  1. Broadens the contribution — the result now covers a setting readers care about (continuum types, dynamics, asymmetry) that the base model excluded.
  2. Defends a load-bearing assumption — it answers the specific "is this knife-edge?" objection that aejmic-identification flagged.

An extension that merely re-derives the base result under a cosmetic re-parameterization fails the test and dilutes the paper.

Placement discipline
  • Core extensions that change the reading: main text. Supporting extensions: online appendix. Do not bury a result-defining extension in supplementary material, and do not pad the main text with extensions that add nothing.
  • A negative extension that explains a boundary of the result often belongs in the main text precisely because it sharpens the contribution; a routine confirmation belongs in the appendix.
Show full SKILL.md (321 more words)Show less

Execution bridge (StatsPAI / Stata MCP)

Run the battery, don't just enumerate it. Full map: execution-with-mcp. AEJ: Micro spans applied and structural micro; the chain below is for the reduced-form / causal lane — structural estimation uses the field's own solvers.

  • Many outcomes / specifications: romano_wolf (step-down FWER, accounts for cross-test correlation) or benjamini_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 exact suggest_function for each — no guessing the battery.
  • Exhibits: etable / did_summary_to_latex from 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.

Checklist

  • Listed candidate extensions; kept only those that broaden the contribution or defend a load-bearing assumption
  • At least one substantive relaxation shows the qualitative result survives (or pins down where it changes)
  • Boundary / knife-edge / tie-breaking cases handled explicitly
  • Concept-dependence stated if the result is specific to one equilibrium notion
  • (Applied) specification/placebo/seed-sensitivity battery run; SEs not asterisks
  • Placement decided: result-defining → main text; supporting → appendix

Anti-patterns

  • An extensions section that adds robustness checks no referee asked for and the result does not need (padding)
  • Hand-waving a knife-edge assumption ("generically this does not matter") without argument
  • Hiding a result-defining extension in the online appendix
  • A robustness table with significance stars
  • Claiming the mechanism is general while every extension quietly re-imposes the key assumption

Worked vignette (illustrative)

A contest-design paper proves the optimal prize structure is winner-take-all under risk-neutral, symmetric players. The earned extensions: (1) risk aversion — show winner-take-all survives up to a curvature threshold, beyond which prizes spread (broadens contribution and locates the edge); (2) asymmetry — show the result fails and explain why (a negative extension that sharpens the mechanism). A non-earned extension would be re-deriving the symmetric case with a trivially different payoff normalization — drop it.

Output format

【Extension menu considered】[...]
【Kept (and why)】broadens contribution / defends load-bearing assumption
【Survives】[relaxation → result holds, with any new condition]
【Breaks / boundary】[case → what changes, handled how]
【Applied robustness】[specs / placebo / seeds] — SEs not asterisks
【Placement】main text: [...]; appendix: [...]
【Next step】aejmic-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-Microeconomics-Skills/skills/aejmic-robustness of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Aejmic 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.

Aejmic Robustness compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Aejmic Robustness this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.6kAutomated safety check: PassMIT
Hypothesis Generationspacering-net/codeg3.9k14 repos~3.6kAutomated safety check: NotesMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT
Last30daysmvanhorn/last30days-skill64k—~7.9kAutomated safety check: NotesMIT

Similar skills

  • Hypothesis Generation

    spacering-net/codeg

    Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.

    3.9k GitHub starsUsed in 14 repos~3.6k tokens
    Research & ScienceAuto-check: notes

  • GitHub Deep Research

    bytedance/deer-flow

    Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.

    84k GitHub starsUsed in 4 repos~1.3k tokens
    Research & ScienceAuto-check passed

  • Nature Paper Card

    Yuan1z0825/nature-skills

    Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.

    47k GitHub starsUsed in 2 repos~2.1k tokens
    Research & ScienceAuto-check passed

  • Content Research Writer

    weapp-tailwindcss/weapp-tailwindcss

    Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.

    1.9k GitHub starsUsed in 25 repos~3.5k tokens
    Research & ScienceAuto-check passed

  • Last30days

    mvanhorn/last30days-skill

    Research what people actually say about any topic in the last 30 days.

    64k GitHub stars~7.9k tokensUpdated yesterday
    Research & ScienceAuto-check: notes

  • Peer Review

    spacering-net/codeg

    Structured manuscript/grant review with checklist-based evaluation.

    3.9k GitHub starsUsed in 17 repos~5.9k tokens
    Research & ScienceAuto-check: notes

More from brycewang-stanford/Awesome-Journal-Skills

All 2,387 skills in this repo

  • Aaag Data Analysis

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…

    1.2k GitHub stars~1.3k tokensUpdated 13 days ago
    Auto-check passed

  • Aaag Literature Positioning

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…

    1.2k GitHub stars~1.3k tokensUpdated 13 days ago
    Auto-check passed

  • Aaag Rebuttal

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…

    1.2k GitHub stars~1.4k tokensUpdated 13 days ago
    Auto-check passed

  • Aaag Research Design

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…

    1.2k GitHub stars~1.4k tokensUpdated 13 days ago
    Auto-check passed

  • Aaag Review Process

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…

    1.2k GitHub stars~1.3k tokensUpdated 13 days ago
    Auto-check passed

  • Aaag Submission

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…

    1.2k GitHub stars~1.6k tokensUpdated 13 days ago
    Auto-check passed

Categories

Questions about Aejmic Robustness

What does Aejmic Robustness do?

A skill your agent uses when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions…. Aejmic Robustness is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions (relaxed assumptions, alternative concepts, perturbations) and applied/experimental robustness.

When should I use Aejmic Robustness?

Aejmic Robustness fits situations like: alternative concepts; perturbations) and applied/experimental robustness.

How do I install Aejmic Robustness in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-robustness -a claude-code`. Or copy the skill folder (AEJ-Microeconomics-Skills/skills/aejmic-robustness in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/aejmic-robustness in your project. Claude Code loads it when a task matches its description.

How do I install Aejmic Robustness in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejmic-robustness -a codex`. Or copy the skill folder (AEJ-Microeconomics-Skills/skills/aejmic-robustness in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/aejmic-robustness in your project. Codex loads it when a task matches its description.

Can I use Aejmic 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 aejmic-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/aejmic-robustness, .gemini/skills/aejmic-robustness, .github/skills/aejmic-robustness and .opencode/skills/aejmic-robustness in your project.

What does Aejmic Robustness need to run?

SKILL.md names no scripts, command-line tools or credentials: Aejmic Robustness is instructions for the agent only.

Does Aejmic 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 Aejmic 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 Aejmic Robustness use?

Aejmic 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 Aejmic Robustness use?

About 1.6k tokens (SKILL.md is roughly 6.6k 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 Aejmic Robustness?

Skills that share tags, products or a category with Aejmic Robustness: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aejmic 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.