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

Aeri Identification

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

A skill your agent uses when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical…

MITAuto-check passedResearch & Science

Install Aeri Identification

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills aeri-identification --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/AER-Insights-Skills/skills/aeri-identification .claude/skills/aeri-identification && 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
aeri-identification
GitHub stars
1.2k
Token cost
~1.7k tokens
SKILL.md length
760 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical…

  • Works in 5 steps: detect_design → recommend → fit with… → Staggered DiD: callaway_santanna /… → IV: effective_f_test + an… → …
  • Parameter identification in a structural model
  • SKILL.md covers When to trigger, The AER: Insights…, Branch paths and Choosing the single in-text…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Aeri Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical design, parameter identification in a structural model, or treatment-effect identification in an experiment. Stress-tests the strategy so it is clean enough to defend in a few pages, before exhibits are finalized.

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 Load testing. 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

  • Parameter identification in a structural model
  • Treatment-effect identification in an experiment

Example prompts

  • “/aeri-identification”

Workflow steps

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

  1. detect_design → recommend → fit with as_handle=true → audit_result to list
  2. Staggered DiD: callaway_santanna / sun_abraham + bacon_decomposition +
  3. IV: effective_f_test + an anderson_rubin_ci (valid under weak instruments),
  4. RDD: rdrobust (bias-corrected) + rddensity / mccrary_test for manipulation.
  5. OVB: oster_delta / sensemakr — how strong a confounder would have to be.

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

Aeri Identification loads about 1.7k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 760 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~103
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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). 760 words, ~1,703 tokens.

Download SKILL.mdSave it as .claude/skills/aeri-identification/SKILL.md (or your agent's skills folder).
name
aeri-identification
description
Use when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical design, parameter identification in a structural model, or treatment-effect identification in an experiment. Stress-tests the strategy so it is clean enough to defend in a few pages, before exhibits are finalized.

Identification — Clean Enough to Defend Short (aeri-identification)

When to trigger

  • The single headline result rests on OLS + controls, or TWFE on staggered timing
  • A structural parameter is estimated but it is unclear what in the data identifies it
  • An experiment's estimand or assumptions are not pinned down
  • You are unsure the identification is clean enough to carry a short paper

The AER: Insights identification bar

A short paper has no room to rescue a weak design with pages of robustness. The identification must be clean, transparent, and self-contained — the central exhibit and one or two sentences should make a non-specialist believe the headline number. Because AER: Insights papers are one insight at AER-level importance, the design is held to AER credibility but expressed with extreme economy: state the data-to-object mapping in one sentence, show the single most convincing diagnostic in-text, and move the rest to the Supplemental Appendix. AEA house style: report standard errors / confidence sets, not significance asterisks, and make everything reproducible for the AEA Data Editor.

Branch paths

Branch A: Empirical causal design (the most common AER: Insights paper)
  • DiD / event study: with staggered adoption move beyond TWFE (Callaway–Sant'Anna, Sun–Abraham, de Chaisemartin–D'Haultfœuille); the single event-study figure with clean leads is often the paper's central exhibit.
  • RDD: density test (Cattaneo–Jansson–Ma), optimal bandwidth, covariate smoothness, bias-corrected CIs; one well-made RD plot can be the whole identification.
  • IV: strong first stage; weak-IV-robust inference (Anderson–Rubin) if needed; defend the exclusion restriction in one tight paragraph.
  • Inference clustered at the assignment level; few-cluster fixes (wild-cluster bootstrap).
Branch B: Experiment (own data)
  • Pre-registration in a recognized registry; report deviations.
  • Randomization balance, attrition (Lee bounds if differential), pre-specified primary estimand, multiple-hypothesis control if more than one outcome.
  • The headline is one pre-registered effect — resist reporting every arm in-text.
Branch C: Structural / parameter identification
  • Name what identifies the key parameter from a specific data moment, in one sentence — a short paper cannot hide behind "the likelihood."
  • Report the sensitivity of the headline parameter to the moment that moves it; Monte Carlo recovery in the appendix.
  • Keep the model minimal (aeri-theory-model) — only what the single insight needs.
Branch D: New fact / measurement
  • Documented construction; show the fact is not a measurement artifact with the one most threatening alternative addressed in-text, others in the appendix.

Choosing the single in-text diagnostic

You have at most five exhibits total and the identification competes with the result for that budget. Pick the one diagnostic that most directly defends the design (the event-study leads, the RD plot, the first-stage, the balance table) for in-text; everything else (placebo cuts, alternative bandwidths, all balance rows) goes to the appendix.

Show full SKILL.md (325 more words)Show less

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the identification claim, don't only argue it. Full map: execution-with-mcp. AER: Insights is a short format built around one decisive result, so the body/appendix split is even tighter — run the design cleanly the first time.

  1. detect_design → recommend → fit with as_handle=true → audit_result to list the checks the design still owes.
  2. Staggered DiD: callaway_santanna / sun_abraham + bacon_decomposition + honest_did_from_result (the pre-trend test is low-power, Roth 2022).
  3. IV: effective_f_test + an anderson_rubin_ci (valid under weak instruments), not a 2SLS t-stat alone.
  4. RDD: rdrobust (bias-corrected) + rddensity / mccrary_test for manipulation.
  5. OVB: oster_delta / sensemakr — how strong a confounder would have to be.

Report the economic magnitude; route the full battery to the appendix; keep every number reproducible. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough. If StatsPAI/Stata are not connected, adapt the vendored resources/code/ skeleton and flag any unverified number.

Checklist

  • Branch chosen; data-to-object mapping stated in one sentence
  • The single most convincing diagnostic is identified for in-text placement
  • Empirical: modern estimator where TWFE would bias; design diagnostic shown
  • Experiment: pre-registered; primary estimand pre-specified; balance/attrition handled
  • Structural: key parameter tied to an identifying moment; sensitivity reported
  • Inference as SEs / confidence sets (no asterisks); clustering level correct
  • The headline claim never exceeds what the identification supports

Anti-patterns

  • Relying on a wall of robustness to compensate for a weak core design (no room for it)
  • TWFE on staggered treatment with no heterogeneity-bias discussion
  • Reporting every experimental arm/heterogeneity split in-text instead of one estimand
  • "The estimator converged" presented as identification (structural)
  • Significance asterisks instead of standard errors / confidence sets

Referee pushback mapped to the fix

  • "OLS with controls is not identification." → Move to a design (DiD/RDD/IV/experiment) or reframe scope; one clean design beats many controls.
  • "Staggered TWFE is biased here." → Re-estimate with Callaway–Sant'Anna / Sun–Abraham; show flat leads in the central figure.
  • "Which moment identifies this parameter?" → One sentence + a sensitivity number; recovery Monte Carlo in the appendix.

Output format

【Branch】empirical / experiment / structural / measurement
【Data-to-object mapping】one sentence
【In-text diagnostic】<the single most convincing exhibit>
【Inference】SEs / confidence sets (no asterisks); clustering level
【To the appendix】placebos / alt bandwidths / full balance / MC recovery
【What it does NOT identify】[…]
【Next step】aeri-robustness (or aeri-theory-model if structural)

© 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 AER-Insights-Skills/skills/aeri-identification of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Aeri Identification 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.

Aeri Identification compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Aeri Identification this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.7kAutomated safety check: PassMIT
What If OracleK-Dense-AI/scientific-agent-skills48k1 repos~2.9kAutomated safety check: PassCC-BY-NC-4.0
Paper ReviewEvoScientist/EvoSkills478—~4.5kAutomated safety check: PassApache-2.0
Data Finderbrycewang-stanford/Auto-Empirical-Research-Skills4.6k—~1.7kAutomated safety check: PassCustom licence
Weakness Scannerflonat/flonat-research146—~1.5kAutomated safety check: PassMIT
Ecta Identificationfranklee16/academic-research-skills2231 repos~1.9kAutomated safety check: PassNone

Similar skills

  • What If Oracle

    K-Dense-AI/scientific-agent-skills

    Supports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions.

    48k GitHub starsUsed in 1 repo~2.9k tokens
    Research & ScienceAuto-check passed

  • Paper Review

    EvoScientist/EvoSkills

    Guides self-review of YOUR OWN academic paper before submission with adversarial stress-testing.

    478 GitHub stars~4.5k tokensUpdated 10 days ago
    Research & ScienceAuto-check passed

  • Data Finder

    brycewang-stanford/Auto-Empirical-Research-Skills

    Find and assess datasets for a research question. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.

    4.6k GitHub stars~1.7k tokensUpdated 5 days ago
    Research & ScienceAuto-check passed

  • Weakness Scanner

    flonat/flonat-research

    Identify recurring weak arguments, unsupported assumptions, and vulnerable inference patterns across a literature corpus.

    146 GitHub stars~1.5k tokensUpdated 11 days ago
    Research & ScienceAuto-check passed

  • Ecta Identification

    franklee16/academic-research-skills

    A skill your agent uses when the bottleneck is identification and inference for an Econometrica manuscript — identification conditions and asymptotic distribution theory for an estimator, or axioms…

    223 GitHub starsUsed in 1 repo~1.9k tokens
    Research & ScienceAuto-check passed

  • Jbv Topic Selection

    franklee16/academic-research-skills

    A skill your agent uses when shaping or stress-testing a research question for the Journal of Business Venturing (JBV) — confirming the entrepreneurial phenomenon is central, picking a…

    223 GitHub starsUsed in 1 repo~1k tokens
    Research & ScienceAuto-check passed

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 Aeri Identification

What does Aeri Identification do?

A skill your agent uses when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical…. Aeri Identification is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the identification argument is the bottleneck for an American Economic Review: Insights (AER: Insights) short-format manuscript — causal identification in an empirical design, parameter identification in a structural model, or treatment-effect identification in an experiment.

When should I use Aeri Identification?

Aeri Identification fits situations like: parameter identification in a structural model; treatment-effect identification in an experiment.

How do I install Aeri Identification in Claude Code?

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

How do I install Aeri Identification in Codex?

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

Can I use Aeri Identification 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 aeri-identification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aeri-identification, .gemini/skills/aeri-identification, .github/skills/aeri-identification and .opencode/skills/aeri-identification in your project.

What does Aeri Identification need to run?

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

Does Aeri Identification 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 Aeri Identification 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 Aeri Identification use?

Aeri Identification 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 Aeri Identification use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 Aeri Identification?

Skills that share tags, products or a category with Aeri Identification: What If Oracle (K-Dense-AI/scientific-agent-skills, 48k stars), Paper Review (EvoScientist/EvoSkills, 478 stars), Data Finder (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars) and Weakness Scanner (flonat/flonat-research, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aeri Identification?

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.