Skill UI

This skill provides comprehensive guidance for authors targeting the AAAI Conference on Human Computation and Crowdsourcing (HCOMP). It helps authors strategically frame, position, and strengthen the evidence of manuscripts focused on crowdsourcing, human-AI collaboration, and collective intelligence, ensuring the work meets the specific academic bar of the venue.

This skill guides authors on positioning their manuscript for the ACM/IEEE International Conference on Human-Robot Interaction (HRI). It helps determine if the work fits the venue, how to re-frame the narrative, and what evidence (user studies, interaction contribution) is expected by HRI reviewers. Ideal for pre-submission strategy and scope calibration in human-robot interaction research.

A comprehensive guide for researchers to determine if their work represents a genuine cross-modal or media-systems contribution suitable for ACM Multimedia (ACM MM). It helps route projects by testing for cross-modality, media system advances, or human-centric results, distinguishing between pure CV, NLP, or system-heavy claims.

A comprehensive guide for structuring the empirical evidence section of top-tier NLP conference papers (e.g., EACL). It mandates rigorous controls, including fair baselines (tuned models, explicit LLM prompts), statistical significance testing (variance, CI), contamination checks, and detailed human evaluation protocols. Use this to elevate your research from mere assertion to scientifically audited proof.

Build and evolve React/Next.js agentic web apps that pair CopilotKit with Microsoft Agent Framework agents hosted in Microsoft Foundry over the AG-UI protocol. Covers wiring choices, native Foundry primitives, tools, human-in-the-loop approvals, generative UI and shared state, local run, azd deployment, and event-stream debugging.

This comprehensive guide helps authors navigate the complex decision of where to submit their Human-Robot Interaction (HRI) research. It outlines critical criteria, including the robot-embodiment and human-in-the-loop tests, to determine the correct venue (e.g., HRI, CHI, ICRA/IROS). Furthermore, it details the five specialized tracks within HRI and advises authors on matching their primary technical contribution to the most suitable academic domain.

A comprehensive guide for authors targeting the IEEE-RAS International Conference on Humanoid Robots. This skill helps frame, scope, and structure research papers in humanoid robotics. It dictates the necessary level of hardware evidence, whole-body control integration, and perception depth required to succeed at this top-tier venue, while distinguishing it from general robotics conferences like ICRA or RoboCup.

A four-tier memory store for AI assistants that promotes recurring facts from transcripts to project context and persona via deterministic recurrence gates, avoiding CLAUDE.md bloat and repeated corrections. Suitable for projects where agents need durable memory that is only committed after human adoption.

Audits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to evidence, reasoning, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.

Transform a legal professional's bounded knowledge, workflow, or judgment patterns into a safe, structured, and reusable AI skill. This tool processes inputs like legal memos, compliance checklists, or negotiation notes to extract core capabilities, risk taxonomies, and review standards. It strictly separates the extracted capability from the individual's personal voice or identity, ensuring full source traceability and mandatory human review points for high-stakes legal work.

A vendor-neutral, benchmark-grounded advisor that routes complex legal tasks to the optimal Large Language Model (LLM). It analyzes the specific legal vertical (e.g., contract drafting, legal research, info extraction) and user constraints (cost, speed, accuracy, jurisdiction) to recommend a primary model, a fallback, and crucial human verification steps. This tool provides decision support, not legal advice.

This tool automates the cleanup and standardization of complex legal documents written in French (Word format). It distinguishes between deterministic corrections (typography, spacing, obvious errors) applied automatically, and context-sensitive revisions (judgment rewrites) that require intelligent human review. It generates a detailed, reversible registry of all changes, ensuring high accuracy for professional legal writing.