Skill UI

This utility allows agents or desks to emit structured signals (e.g., hands-up, blocked, done, checkpoint) in JSON format. These signals are crucial for real-time dashboard consumption, providing the operator or coordinator with immediate, actionable insights into the work status, disagreement points, or required attention levels of various work units. It also supports optional 'outcome signals' for self-assessment calibration.

This guide provides best practices for authors submitting to top-tier technical conferences. It clarifies the critical distinction between core, review-essential arguments (which must stand alone in the main paper) and supporting evidence (such as formal proofs, extra data analyses, or methodological details) suitable for an optional supplementary document. It also covers anonymity best practices and distinguishing between different submission types.

A comprehensive guide detailing how to package and present research artifacts—including code, hardware designs, and datasets—for major academic conferences. It outlines best practices for both initial review-time evidence and long-term public reuse, ensuring reproducibility and maximizing the chances of adoption by future builders.

A comprehensive guide detailing the mandatory and optional evaluation phases for academic security artifacts, such as those required for USENIX Security. It covers Phase-1 (availability) checks and Phase-2 (functionality, reproducibility) requirements. Provides best practices for structuring code, managing technical hazards (e.g., dangerous-by-default behavior), and ensuring verifiable, reproducible results for peer review.

This guide outlines the strict formatting and structural guidelines for submitting security conference papers (like USENIX Security). It helps authors determine which material—core mechanisms, proofs, or supplementary data—must remain in the main body to guarantee review visibility, versus what can be safely demoted to optional appendices or external artifacts.

A comprehensive guide for authors submitting to WACV, detailing the strategic differences between the optional one-page Round 1 rebuttal and the mandatory change summary accompanying a Revise-and-Resubmit. It provides best practices for addressing reviewer concerns, maintaining anonymity, and accurately documenting revisions.

This guide models the comprehensive two-round, journal-style peer review process used at major computer vision conferences like WACV. It details the distinct stages: Round 1 outcomes (Accept, Revise and Resubmit, Reject), the optional R1 rebuttal phase, and the final R2 decision. It emphasizes that the most critical phase for authors is executing high-quality revisions during the Revise-and-Resubmit stage, rather than solely relying on rebuttals.

Comprehensive guide detailing the end-to-end academic submission workflow for the WACV conference. This specialized workflow accounts for the two-round submission model, including key branching points like Round 1 reviews, optional rebuttals, Revise-and-Resubmit stages, Round 2 revisions, and final camera-ready preparation, which single-deadline plans often miss.

A comprehensive workflow guide for managing the entire academic research cycle of a major conference, such as the Web Conference. It details key milestones, backward planning strategies from abstract deadlines, fallback options (Short Papers, Web4Good), and capacity planning tips to ensure timely and successful submission and publication.

Provides decision support for mapping diagnoses and procedures extracted by OpenMed to standardized ICD-10-CM and ICD-10-PCS codes. This skill suggests candidate codes along with detailed clinical rationale, helping human coders narrow down options, route findings to specific chapters, and pre-fill encounter records. Note that the output is advisory and requires mandatory validation by a certified medical coder.

This tool performs a comprehensive analysis of AI configuration file evolution within a Git repository. It tracks when specific AI configs were first introduced, charts monthly commit velocity related to AI features, highlights key PRs that shaped the development, and synthesizes the project's AI maturity phases. Ideal for mapping AI adoption timelines and assessing technical maturity.

Manage stateful proof projects with run directories, local source bookkeeping, manual GPT Pro handoff packages, optional DeepSeek review, and rigorous audit gates.