Skill UI

A comprehensive guide for designing and implementing production-grade microservices using gRPC in Go. Covers best practices for API contract standardization with Protobuf and Buf, securing service-to-service communication via mTLS, and integrating deep observability using OpenTelemetry interceptors. Ideal for building high-performance, reliable internal APIs.

Datamol wraps RDKit with Pythonic APIs tailored for drug discovery, offering SMILES/SELFIES/InChI parsing, standardization, descriptor and fingerprint calculation, clustering, 3D conformer workflows, and parallel/cloud-aware batch I/O while returning native rdkit.Chem.Mol objects.

This skill generates formal, audit-ready Standard Operating Procedures (SOPs) suitable for regulated industries, ISO certification, or internal process standardization. It structures the document with defined sections including Purpose, Scope, Definitions, Responsibilities, detailed Step-by-step Procedures, Quality Checks, and Non-Conformance handling, ensuring compliance and clarity for operational scaling.

This skill serves as a senior QA automation architect to migrate and convert UI test automation scripts between popular frameworks, including Selenium, Playwright, Puppeteer, and Cypress. It handles complex conversions by applying API mapping, lifecycle adjustments, and pattern standardization, allowing users to port tests from one framework to another efficiently.

This comprehensive guide provides detailed formatting standards for academic manuscripts, covering tables (three-line format), formulas, and figures. It ensures that submitted research adheres to strict journal layout requirements, emphasizing high information density, standardization, and clarity within stringent page limits.

This guide details the critical steps and changes required to transform a reviewed SIGIR submission into the final Version of Record published via ACM Digital Library. It covers technical requirements, metadata standardization (CCS, keywords), conflict resolution, and adhering to publishing timelines and copyright protocols (e-rights, TAPS).

This skill automatically detects and extracts tabular laboratory panels from diverse sources, including scanned images, photos, and delimited files (CSV/TSV). It converts complex visual data into clean, structured rows, capturing the test name, measured value, unit, reference range, and abnormal flag. It is essential for preparing medical data for subsequent standardization using LOINC and UCUM, and for mapping into FHIR resources.

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.