| name | econ-auto-research-pipeline |
| description | Automated economics and management research governance workflow for Codex. Use when the user asks to start, organize, audit, automate, or advance an empirical research project in economics, finance, management, strategy, organization, labor, innovation, information systems, AI adoption, digital economy, or related social-science fields. Integrates ARIS-style overnight research loops, reproducible data and Stata-first empirical workflows, systematic literature-review protocols, topic/design go-no-go gates, independent peer review, revision loops, external-review triage, integrity verification, and handoff documentation. |
Econ Auto Research Pipeline
Use this skill as the main operating system for an economics or management research project. It is a research governance system, not a paper generator.
It combines:
- ARIS-style automation: idea -> plan -> execution -> review -> narrative -> manifest.
- Reproducible empirical discipline: immutable raw data, scripted cleaning, Stata-first reported regressions, logs, provenance, handoff.
- Academic pipeline quality gates: deep research, paper drafting, integrity checks, two-stage review, revision roadmap, final verification.
- Systematic literature-review discipline: documented search strategy, screening log, source-density thresholds, citation chaining, gap map, and source-to-claim traceability.
- Reflexive research governance: topic tournament, decision log, peer review at design/results/manuscript stages, and explicit GO / REVISE / PIVOT / KILL decisions.
Non-Negotiable Rule
Do not run a linear "topic -> data -> regression -> paper" pipeline. Every major step must leave a decision artifact and must be allowed to stop, pivot, or restart. A polished PDF is not success unless topic contribution, literature position, data granularity, identification strength, empirical integrity, and peer review gates are all documented.
Start Here
-
Inspect the project root.
- Run
pwd, rg --files, and find . -maxdepth 2 -type d.
- Read existing
README, PROJECT_LOG, RESEARCH_BRIEF, RESEARCH_DESIGN, DATA_DICTIONARY, REPLICATION_README, and AGENTS.md if present.
- Report the current state before major edits.
-
Classify the entry point.
- New idea: start with research question and literature scoping.
- Existing data: audit provenance, structure, and sample construction.
- Existing code: map pipeline entry points and logs.
- Existing results: run empirical integrity and claim checks.
- Existing draft: run manuscript integrity and peer review.
- Reviewer comments: build a revision roadmap and response plan.
-
Load references as needed.
- Research governance, topic tournament, gate decisions, or post-mortem:
references/research-governance.md.
- Project setup or messy files:
references/reproducibility-standards.md.
- Stata regressions or final tables:
references/stata-first-pipeline.md.
- Literature search, systematic review, citation chaining, source-density gates, or top-journal literature positioning:
references/literature-review-protocol.md plus references/deep-research-method.md.
- Paper writing or revision:
references/manuscript-pipeline.md.
- Chinese top-journal polishing: trigger
chinese-econ-paper-polisher or load its style reference when drafting Chinese manuscripts.
- Review, integrity, or claim validation:
references/review-and-integrity.md.
- External review services such as Stanford Agentic Reviewer / PaperReview.ai:
references/external-review-systems.md.
- AI-assisted research operating rules from Mihail Velikov's AI in Business & Economic Research wiki:
references/ai-econ-wiki-integration.md.
- Overnight automation:
references/automation-runbook.md.
- Artifact names and handoff:
references/artifact-contract.md.
Integrated Workflow
Stage -1: Research Governance Contract
Create or update process artifacts before substantive execution:
memos/research_tournament.mdmemos/decision_log.mdmemos/literature_review_protocol.mdmemos/ai_workflow_audit.mdmemos/review_report.mdmemos/revision_roadmap.md
Gate rule: if the project lacks these artifacts, initialize them before drafting a paper or running new formal regressions.
Apply the AI-econ-wiki operating rules:
- Treat the repo as context: important state must be in files, not chat.
- Use Prompt -> Plan -> Review -> Revise for nontrivial work.
- Use fresh-context review for design, method, data, and manuscript gates where possible.
- Record AI use, privacy/cost decisions, and skipped gates in
memos/ai_workflow_audit.md.
Stage 0: Project Intake
Create missing project scaffolding conservatively. Do not duplicate an existing structure.
Deliver:
- Project map.
- Missing artifact list.
- Immediate risks.
- Next safe action.
Stage 1: Topic Tournament And Research Question
For a new or weakly specified project, compare at least three candidate research questions unless the user explicitly forbids alternatives.
Score each candidate on:
- substantive importance;
- theoretical contribution;
- literature gap credibility;
- data granularity and availability;
- identification strength;
- top-journal fit;
- reproducibility burden;
- risk of being a "regression-shaped essay."
Deliver memos/research_tournament.md and record the decision in memos/decision_log.md.
Gate verdict:
GO: advance to design.REVISE: refine question before data work.PIVOT: choose another candidate.KILL: stop this direction.
Stage 2: Research Design Gate
Turn the topic into a precise economics or management question.
Require:
- Unit of analysis.
- Treatment/exposure/key explanatory variable.
- Outcome.
- Mechanism.
- Identification boundary: causal, quasi-causal, descriptive, predictive, or mechanism evidence.
- Feasible data path.
Deliver memos/research_design_brief.md.
Gate rule: do not collect data or run regressions until the design memo states what evidence would falsify or severely weaken the project.
Stage 3: Literature Review And Positioning Gate
Build a source matrix, not a pile of citations.
Deliver:
memos/literature_review_protocol.md.memos/literature_matrix.md.- Search strategy and inclusion/exclusion rules.
- Screening counts, rejected-source reasons, and saturation status.
- Competing explanations and gap map.
- Dangerous prior art list.
For Chinese top-journal writing, literature narration must mostly use natural inserted citations and problem-oriented synthesis, not a mechanical "Author (Year) found..." pile.
Gate rule: if literature density, journal quality, Chinese/English balance, or dangerous prior art coverage is insufficient, return to literature search before empirical execution.
Stage 4: Data And Design-Fit Gate
Make the project reproducible before chasing results.
Require:
- Raw data immutable.
- Derived data scripted.
- Metadata, codebook, sample rules, row counts, and checksums where useful.
- Every final dataset mapped to input files and generating scripts.
- Explicit judgment on whether data granularity matches the research question.
Deliver data/metadata/data_provenance.md or update equivalent.
Gate rule: if available data are too coarse for the claimed contribution, downgrade the claim, redesign the question, or pivot.
Stage 5: Empirical Plan Gate
Create a claim-driven empirical plan.
Deliver:
memos/empirical_plan.md.- Specification ladder.
- Inference plan.
- Robustness and placebo checklist.
- Mechanism and heterogeneity plan.
- Method-specific audit checklist: DiD / IV / RD / panel FE / text-as-data / prediction-ML as applicable.
- Pre-analysis lock: outcome hierarchy, timing, sample rules, controls, fixed effects, clustering, and falsification criteria.
- What would falsify the story.
Gate rule: do not write manuscript results before a methods-review pass has challenged identification, measurement, controls, fixed effects, clustering, and table format.
Stage 6: Implementation And Runs
Use existing code patterns.
Default data flow:
data/raw -> scripts/build or scripts/utilities -> data/final/*.dta -> do/*.do -> output/tables + output/figures + output/logs
Formal reported regressions should be Stata do-files unless the user says otherwise.
Deliver:
- Updated scripts/do-files.
- Logs under
output/logs.
- Tables under
output/tables.
- Figures under
output/figures.
- Chronological update in
PROJECT_LOG.md.
Stage 7: Empirical Integrity And Internal Review Gate
Do not write paper claims until this gate passes.
Check:
- Leakage.
- Sample filters.
- Metric or variable construction.
- Fixed effects and clustering.
- Baseline fairness.
- Robustness coverage.
- Whether causal language exceeds design.
- Whether top-journal table format is met: columns are regressions/specifications, rows are coefficients and standard errors, and controls/fixed effects/sample sizes/R-squared/clustering are reported.
- Whether AI-assisted data construction, code generation, or labeling has been audited and recorded in
memos/ai_workflow_audit.md.
- Whether text-as-data or LLM-coded variables have human-audited labels, prompt/version logs, and leakage checks.
Deliver memos/empirical_status.md.
Also run a multi-perspective internal review before manuscript drafting. If verdict is PIVOT or KILL, stop or redesign.
Stage 8: Manuscript Pipeline
Write from evidence, not vibes.
Deliver:
- Paper outline and claim-evidence map.
- Draft sections in
paper/.
- Citation audit.
- Figure/table integration notes.
- Limitations and scope conditions.
- For Chinese submissions, run
chinese-econ-paper-polisher before review. Require terminology unification, de-AI rewriting, empirical narration correction, and top-journal risk notes.
Stage 9: Peer Review And Revision
Run a multi-perspective review:
- Editor-in-chief: contribution and journal fit.
- Methods reviewer: identification, statistics, reproducibility.
- Domain reviewer: literature and theory.
- Practical/policy reviewer: implications and external validity.
- Devil's advocate: strongest counterargument and overclaiming.
Deliver:
memos/review_report.md.memos/revision_roadmap.md.memos/chinese_polish_report.md for Chinese manuscripts.- Re-review after revisions.
Gate rule: a final manuscript requires at least one review report and one revision roadmap. If serious issues remain, label the output as a working draft, not submission-ready.
Stage 10: Optional External Review Triage
External AI review tools may be used only as supplemental signal after internal review. For PaperReview.ai / Stanford Agentic Reviewer, remember:
- it currently accepts PDF upload plus email and analyzes only the first 15 pages / 10MB;
- it warns AI reviews can contain errors;
- its own notes say arXiv grounding makes it more accurate in AI-like fields and less accurate elsewhere, and it supports English-language papers for now.
For Chinese economics/management manuscripts, do not treat it as a primary referee. Use it only after creating an English synopsis or translated draft and record limitations in memos/external_review_log.md.
Stage 11: Final Handoff
Update:
README.md.PROJECT_LOG.md.MANIFEST.md.memos/handoff_brief.md.
End every substantial session with current question, data, scripts, latest results, limitations, next steps, changed files, and commands run.
Guardrails
- Never overwrite raw data.
- Never manually edit derived datasets.
- Never bury failed diagnostics.
- Never present exploratory correlations as causal effects.
- Never finalize claims without code, logs, evidence, and review status.
- Never skip topic/design/literature gates because a user asked for a polished paper quickly; label any rushed output honestly.
- Never write process/meta commentary inside the manuscript body (for example, "for Chinese top journals, this wording...").
- Stop before paid compute, remote credentials, destructive cleanup, or broad irreversible changes.
