skills/50-brycewang-aer-skills/skills/aer-workflow/SKILL.md
Use when deciding which AER-skills sub-skill to use next, or when sequencing manuscript work from topic selection through rebuttal for the American Economic Review, AER:Insights, or AEJ journals. Routes — does not replace — the specialized skills.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research aer-workflowInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This is the router. It does not replace any specialized skill. It tells you which one to use next, and in what order.
Default assumption: unless the user names a different venue, the manuscript targets AER, AER: Insights, or an AEJ journal — not a finance journal, not a generic economics field journal, and not a working-paper repository.
Use:
aer-topic-selection when the project is new, when the user is undecided between AER / Insights / an AEJ, or when the contribution sentence cannot be written in one lineaer-identification when the empirical design is the bottleneck — DiD, IV, RDD, SCM, shift-share, event study, RCT analysisaer-robustness when the main results exist but referee-anticipating checks (placebo, heterogeneity, mechanism, alternative samples) are missing or weakaer-introduction when drafting or rewriting the introduction, or when the abstract is over 100 wordsaer-tables-figures when regression tables are inconsistent, oversized, footnote-bloated, or do not match AER house styleaer-replication when preparing the AEA Data and Code Availability deposit, writing the README, or auditing reproducibility before acceptanceaer-submission when running the final preflight before clicking submit — length, format, cover letter, conflictsaer-rebuttal when reviewer comments exist and a point-by-point response letter plus aligned manuscript edits are neededFor most empirical AER-track manuscripts, prefer this order:
aer-topic-selection — fix the contribution sentence and the target venue before anything elseaer-identification — stress-test the design; if it fails here, no later skill saves the paperaer-robustness — anticipate the three robustness checks the median referee will demandaer-introduction — only now write the five-paragraph intro and the 100-word abstractaer-tables-figures — finalize the main exhibits in AER house styleaer-replication — assemble the deposit package while results are still fresh in codeaer-submission — final preflight: length, format, cover letter, COIaer-rebuttal — after external review, revise manuscript first, then write the letter against the revised versionIf the user says...
aer-topic-selectionaer-identificationaer-identification (weak-IV branch)aer-robustnessaer-introductionaer-tables-figuresaer-replicationaer-submissionaer-rebuttalaer-introduction — the introduction conventions differ (no heading, five-paragraph Head formula, ≤ 100-word abstract)aer-replication — the AEA policy is unusually strict and the openICPSR workflow is specificaer-topic-selection because "I already know this is an AER paper" — desk rejection at AER is ~60% and the top-5 bar is cross-subfield interest, not technical competenceWhenever this skill is invoked, end with:
NEXT SKILL: <aer-skill-name>
REASON: <one sentence>
INPUTS NEEDED: <list of artifacts the next skill needs>
This keeps the agent loop tight when the user runs multiple skills in sequence.
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.