Skill UI

PyLabRobot is a vendor-agnostic, pure Python SDK designed for autonomous and automated laboratory workflows. It provides a unified interface to control a wide array of laboratory equipment, including liquid handling robots (Hamilton, Opentrons, Tecan), plate readers, pumps, shakers, and incubators. Ideal for developing complex, multi-device, reproducible protocols and simulating experiments before physical execution.

A framework-agnostic, builder-based SEO system designed for React and React Native-for-web applications. It centralizes site identity (title, description, OG tags) in a single source of truth, ensuring all metadata, canonical URLs, and structured data (JSON-LD, sitemap, robots.txt, RSS) are consistent, machine-readable, and automatically generated for every route.

A comprehensive skill for generating keyword-driven automated test scripts using Robot Framework. It supports front-end UI testing via SeleniumLibrary, robust API integration using RequestsLibrary, and complex custom keywords. Ideal for building end-to-end and functional test suites.

Provides an expert framework for authors submitting to the Conference on Robot Learning (CoRL). It guides writers on how to re-frame general computer science manuscripts into specialized, robust robot-learning narratives. The guide covers defining the contribution type, establishing the evidence bar (from simulation to real-world transfer), and strategically positioning the work against major robotics conferences like ICRA and IROS.

This comprehensive guide establishes a rigorous framework for ensuring reproducibility in robot learning research. It details how to document both the "rerunnable half" (software, simulation versions, training configs, seeds) and the "auditable half" (physical hardware specs, sensors, firmware). Adhering to these standards allows experts to verify and rebuild the experimental results.

A comprehensive guide to strategically routing robotics research projects. This skill helps determine whether a project is best suited for ICRA, IROS, CoRL, RA-L, or other specialized venues. It evaluates your work based on the physical embodiment test, contribution type (e.g., HRI, manipulation, perception), and provides a decision framework between direct conference submission and journal publication.

This guide provides a comprehensive framework for positioning robotics research papers for top-tier conferences like IROS, ICRA, and CoRL. It teaches authors how to audit novelty by comparing their work against multiple related systems—not just the nearest component—and how to handle archival overlap, concurrent work, and anonymity requirements in double-blind review processes. It emphasizes defining the system contribution across multiple robotics lanes.

A rigorous framework for designing reproducible and scientifically sound experiments in robotics and AI, specifically for academic publication (e.g., RSS). It guides users to shift focus from simple system demonstration to testing a falsifiable scientific claim. Key areas covered include deriving conditions from a claim, establishing hardware trial protocols, managing simulation vs. real-world evidence splits, and performing detailed failure attribution analysis.

This skill provides a detailed framework for researchers to determine the most suitable venue (e.g., RSS, ICRA, CoRL, IROS) for their robotics project paper. It teaches how to shift focus from merely demonstrating a system's capabilities to articulating a precise, testable scientific claim, ensuring the work is optimally presented to the target academic community.

This guide provides a comprehensive project management framework for submitting research to major robotics conferences, particularly RSS. It maps out the complex annual cycle, from abstract submission to final presentation, detailing critical deadlines, required milestones (like hardware trials and writing drafts), and fallback options at sibling venues (IROS, CoRL, ICRA). Essential for researchers managing time-sensitive academic pipelines.

This skill guides authors on positioning foundational and conceptually general robotics research for submission to The International Journal of Robotics Research (IJRR). It evaluates the manuscript's depth, generality, and conceptual framework, helping authors re-frame single-demonstration results into field-advancing principles. It also assists in choosing between IJRR and competing venues like IEEE Transactions on Robotics (T-RO).

This skill provides a portable, framework-agnostic SEO system for React or React Native-for-web frontends. It centralizes site metadata in a constants module, derives canonical URLs, and generates per-route metadata including titles, descriptions, Open Graph, and Twitter cards. It also produces sitemaps, robots rules, RSS feeds, and typed JSON-LD without requiring manual meta tag copy-pasting.