bg-szy

Use when creating new skills, editing existing skills, or verifying skills work before deployment

Updated skill

Build tools that agents can use effectively, including architectural reduction patterns

Guide for using pytest-mock plugin to write tests with mocking. Use when writing pytest tests that need mocking, patching, spying, or stubbing. Covers mocker fixture usage, patch methods, spy/stub patterns, and assertion helpers.

Group related keywords into topic clusters. Create content hub architecture recommendations and internal linking strategies.

Aplica as cores e tipografia oficiais da marca Anthropic a qualquer artefato que possa se beneficiar da identidade visual da Anthropic. Use-o quando cores da marca, diretrizes de estilo, formatação visual ou padrões de design da empresa forem aplicáveis.

Automate GitHub workflows with AI assistance. Includes PR reviews, issue triage, CI/CD integration, and Git operations. Use when automating GitHub workflows, setting up PR review automation, creating GitHub Actions, or triaging issues.

Provides Go patterns for type-first development with custom types, interfaces, functional options, and error handling. Must use when reading or writing Go files.

Fluxo de trabalho de documentação de API para gerar especificações OpenAPI, criar guias para desenvolvedores e manter uma documentação de API abrangente.

Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), MSIngs, MANTIS, MSIPanel, MSIDetect, and ngsMSI for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distingu

Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support

Searches for non-coding RNA homologs and classifies RNA families using Infernal covariance model searches against the Rfam database. Identifies structured RNAs by sequence and secondary structure conservation. Use when querying sequences against Rfam, building custom covariance models for novel RNA families, or classifying non-coding transcripts by family.