Use esta habilidade ao escrever código que chama a API Gemini para geração de texto, chat multi-turno, compreensão multimodal, geração de imagens, respostas em streaming, tarefas de pesquisa em segundo plano, chamada de funções, saída estruturada ou migração da antiga API generateContent. Esta habilidade cobre a API Interactions, a maneira recomendada de usar modelos e agentes Gemini em Python e TypeScript.
Esta skill fornece diretrizes e práticas recomendadas para desenvolvedores que desejam integrar a API Gemini em seus projetos, seja para geração de texto, chat multi-turno, compreensão multimodal, geração de imagens, respostas em streaming, tarefas de pesquisa em segundo plano, chamada de funções, saída estruturada ou migração da API generateContent legada. Ela abrange especificamente a API Interactions, que é a abordagem recomendada para usar modelos e agentes Gemini em Python e TypeScript. A skill detalha como iniciar sessões de chat, configurar parâmetros de modelo, lidar com entradas multimodais e executar chamadas de função de forma eficiente. Além disso, orienta sobre como obter saídas estruturadas e processar respostas em streaming, garantindo uma integração robusta e performática com os recursos mais modernos da plataforma Gemini.
npx skills add https://github.com/google-gemini/gemini-skills/tree/main/skills/gemini-interactions-apiInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Use esta habilidade ao escrever código que chama a API Gemini para geração de texto, chat multi-turno, compreensão multimodal, geração de imagens, respostas em streaming, tarefas de pesquisa em segundo plano, chamada de funções, saída estruturada ou migração da antiga API generateContent. Esta habilidade cobre a API Interactions, a maneira recomendada de usar modelos e agentes Gemini em Python e TypeScript.
This repo contains 4 individual skills — each has its own dedicated page.
Use this skill when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.
Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, live translation, and all Live API configuration options. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).
Use this skill for generative video editing, text-to-video, image-referenced video generation, first-frame-to-video, first-and-last-frame transitions, and video extensions using Gemini Omni 1.1 Flash (gemini-omni-1.1-flash) via the official google-genai SDK. Includes workflows for pre-processing/optimizing high-resolution or long source videos with ffmpeg, stripping audio for full sound regeneration, and handling turn-by-turn video editing and parallel execution.
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.