Skill UI

This guide provides best practices for presenting tables and figures in academic manuscripts, specifically tailored to the requirements of the Journal of Public Administration Research and Theory (JPART). It emphasizes that exhibits must be self-contained, focusing on communicating mechanisms and effect magnitudes rather than just statistical significance. It also guides authors on managing word limits by strategically defining the role of core findings versus supplementary material.

This guide provides comprehensive methodology for advanced empirical analysis in Public Economics, particularly for manuscripts using large administrative or register microdata. It covers advanced topics like estimating behavioral elasticities, calculating welfare metrics (MVPF, DWL), and ensuring robust causal identification strategies. It emphasizes translating raw coefficients into policy-relevant quantities with rigorous uncertainty quantification.

A comprehensive, step-by-step preflight checklist designed for authors submitting manuscripts to top-tier scientific journals. It ensures thorough validation across all required components, including the mechanistic narrative, structural data integrity, statistical rigor (QSA), figure quality, and proper data/code deposition (DOIs). It serves as the ultimate gatekeeping mechanism before final submission.

This skill helps assess whether a manuscript in solid-earth, ocean, atmospheric, or planetary sciences meets the high conceptual and systemic standards required for top-tier geoscience journals like Nature Geoscience. It guides authors to re-frame local findings into global, Earth-system processes, focusing on cross-disciplinary coupling, mechanistic advances, and robust data documentation. It is a conceptual fit tool, not a submission guide.

This comprehensive framework guides the rigorous design and defense of research in public administration. It covers essential causal inference methodologies, including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RD), and various experimental designs on bureaucrats and citizens. Use this guide when defining identification, responding to reviewer critiques regarding causality, or pre-registering a study, ensuring the design is both academically sound and practically relevant to public policy.

A comprehensive guide and heuristic tool for assessing whether an academic manuscript is suitable for high-level public administration and policy journals, specifically referencing Public Administration and Policy Review. It details required scope, suitable methodologies (e.g., policy evaluation, case studies, mixed methods), structural requirements (anonymity, abstract formatting), and common rejection pitfalls to guide authors toward rigorous academic writing.

A comprehensive skill designed for authors targeting Science Signaling, a leading journal in cellular signal transduction. This tool provides guidance on the journal's scope, required mechanistic depth, quantitative rigor, house style, and specific evidence standards (e.g., loss/gain-of-function, in vivo evidence). It is crucial for venue selection and restructuring manuscripts to fit the high standards of AAAS Science family publications.

Provides comprehensive guidelines for achieving high levels of scientific reproducibility for academic papers, particularly those in systems metrics. It covers mapping claims to verifiable evidence, ensuring simulators are seeded and deterministic, and documenting measurement provenance to allow reviewers to independently verify all reported results.

This skill guides authors on positioning information retrieval (IR) work for the Text REtrieval Conference (TREC). It functions as a venue-selection and manuscript re-framing tool, ensuring the submission aligns with TREC's focus on shared evaluation tracks, test collections, and NIST-style benchmarking. It helps authors structure evidence, understand reviewer expectations, and distinguish the work from general CS conference submissions.

This tool assists researchers in assembling and rigorously validating a complete replication package for academic submission. It checks the master script, pinned environment, data plan, and methodology against specific journal policies, ensuring that every reported number is reproducible and deterministic, preventing 'my machine' errors.

This skill performs an adversarial second pass to scan already de-identified clinical text for residual identifiers (PHI/PII). It combines deterministic regex checks (SSN, phone, dates) with a model-based PII detection rerun. It scores severity and implements a hard block rule: any detected leak prevents data release, ensuring the highest standard of data privacy and compliance.

This skill serves as a deterministic internal downloader for image URLs extracted from comprehensive web search results. It receives normalized media slots and search output via stdin, utilizing Python HTTP APIs to download direct image links. The process includes validating MIME types and saving files accurately into the configured local project directory, ensuring reliable asset retrieval without relying on sandboxed shell tools.