Skill UI

This skill offers two complementary workflows for locally checked-out codebases. Documentation mode creates a definitive, cited architecture document ideal for onboarding and system research. Modernization mode then builds upon this documentation, generating a phased, safety-laddered plan to upgrade, migrate, or rewrite legacy systems. It emphasizes local-first analysis for maximum accuracy.

A comprehensive guide for preparing research artifacts (code, data, prompts, models) for EACL submissions. It details the two stages: an anonymized supplement for the initial review (ARR) and a fully licensed, public release for post-acceptance. Emphasis is placed on reproducibility, responsible NLP practices, and proper documentation.

This guide details the requirements for creating a comprehensive replication package for manuscripts submitted to Econometric Society journals. It ensures full reproducibility of all results, including code, data provenance, and parameter settings, adhering to the journal's Data and Code Availability Policy. Key components include a master script, reproducible data, and detailed documentation.

This guide provides expert knowledge on the history, etymology, and correct modern usage of the em dash (—). It covers various punctuation marks—including commas, semicolons, and colons—and offers specific guidelines on when to use them in professional writing, technical documentation, and code comments. It emphasizes adapting punctuation rules for different media types.

Provides comprehensive guidelines for authors submitting empirical, quantitative, or theoretical growth papers. It details how to package data sources, code pipelines, calibration files, and historical/geospatial artifacts to meet stringent reproducibility standards for publishing journals.

A comprehensive guide and package structure for preparing empirical law and economics manuscripts for journal submission, ensuring full data and code reproducibility prior to publication. It mandates the assembly of data files, transformation scripts, a master execution script, and detailed README documentation, explicitly addressing the unique challenges of restricted or proprietary legal data sources (e.g., sealed court records).

A comprehensive guide for authors submitting policy evaluation manuscripts to academic journals. It outlines the rigorous standards required to ensure full research reproducibility, detailing the process of archiving data and code in public repositories, creating master scripts, and providing documentation for restricted administrative data access.

This guide helps authors prepare manuscripts for high-impact journals, specifically detailing the mandatory requirements for data and code transparency (e.g., JPART). It outlines how to build a complete, reproducible package, including master scripts, documentation (README), data availability statements, and managing potential data restrictions, ensuring publication acceptance is not stalled by materials.

This guide outlines best practices for Nature Geoscience authors, detailing how to separate essential narrative (Main Text) from comprehensive, reproducible documentation (Online Methods). It emphasizes grounding every quantitative claim, quantifying uncertainty, and ensuring full data and code availability to meet high academic standards and pass rigorous peer review.

This guide outlines the rigorous requirements for preparing a reproducible package for Quantitative Economics (QE) journal submissions. It details the strict standards set by the Econometric Society Data Editor, covering raw data, code, documentation, and handling complex data exemptions to ensure the submission passes the pre-acceptance reproducibility check (DCAS compliant).

This guide establishes the rigorous policy for submitting computational and empirical papers to academic journals. It mandates that authors provide sufficient data, source code, and detailed documentation (including execution order, random seeds, and OS used) to ensure that research findings can be fully reproduced by others, adhering to global standards like Option C.

A comprehensive guide for authors submitting to SCI journals, detailing best practices for making research code and data available. It addresses how to proactively provide reproducible materials, structured documentation, and honest availability statements, even when formal 'Artifact Evaluation' badges are not mandatory. It helps authors improve the robustness and impact of their scientific findings.