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Execute statistical analysis pipeline, generate tables and figures
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
Reference for configuring, launching, and monitoring research iteration loops and analysis polish loops
Verifies the analysis pipeline runs end-to-end, outputs match expectations, and LaTeX compiles
Hands-on QA of the research analysis pipeline. Use whenever the user asks to verify the pipeline end-to-end, check output file integrity, validate table and figure generation, test data processing, or verify LaTeX compilation. Triggers on phrases like "test the pipeline", "QA the analysis", "check the outputs", "verify the tables", "run end-to-end", "does the paper compile", or any request to validate a research pipeline.
Define research question, hypotheses, methodology outline, and literature gap
Decompose a research question into cook-it-ready epic beads with methodology specifications
Comprehensive playbook for building rigorous, publication-quality research papers. Covers the full research output sequence from paper structure and statistical reporting through table formatting, figure design, LaTeX conventions, academic writing quality, and pre-submission review.
| name | Work Analysis |
| description | Execute statistical analysis pipeline, generate tables and figures |
Run the analysis pipeline from data to outputs. Every result must be reproducible -- fixed seeds, documented transformations, and a reproducibility manifest. This sub-skill is invoked by the work router -- it does not run standalone.
Deploy analysis agents:
.claude/agents/drl/analyst.md -- executes regressions and generates outputsbd show <epic> for the variable operationalization tablesrc/data/loaders.pysrc/data/cleaners.pyExecute in order, outputting to paper/outputs/tables/ and paper/outputs/figures/:
src/analysis/descriptive.py): summary stats, correlations, distributionssrc/analysis/econometrics.py): implement each model equation per the plan, follow variable operationalization exactlysrc/analysis/robustness.py): alternative specifications, sensitivity analysesLog ALL methodological decisions to docs/decisions/ using the ADR template:
Use /drl:decision for guided logging.
uv run python -m src.orchestrators.repro
paper/outputs/tables/paper/outputs/figures/src/data/src/analysis/src/visualization/paper/outputs/tables/, paper/outputs/figures/