200 件 ・ 関連度順
概要と使いどころ
Especialista em integrar APIs de terceiros com autenticação adequada, tratamento de erros, limitação de taxa e lógica de retry. Use para integrar APIs REST, endpoints GraphQL, webhooks ou serviços externos. Especializado em fluxos OAuth, gerenciamento de chaves de API, transformação de requisições/respostas e construção de clientes de API robustos.
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Quando o usuário quer otimizar onboarding pós-signup, ativação de usuários, experiência de primeira execução ou time-to-value. Use também quando o usuário menciona "fluxo de onboarding", "taxa de ativação", "ativação de usuários", "experiência de primeira execução", "empty states", "checklist de onboarding", "aha moment" ou "experiência do novo usuário". Para otimização de signup/registro, veja signup-flow-cro. Para sequências de email contínuas, veja email-sequence.
日本語の概要は準備中です。原文の説明を表示しています。
Renderize diagramas SVG limpos em estilo blueprint a partir de specs JSON. Use quando usuários pedirem para desenhar, esboçar ou diagramar um fluxo de requisição, rede neural, bloco transformer, arquitetura de sistema, máquina de estados, pipeline de dados, ou qualquer visual técnico de nós e arestas que queiram como SVG para docs, READMEs, posts ou slides.
日本語の概要は準備中です。原文の説明を表示しています。
Quando o usuário quer otimizar, melhorar ou aumentar conversões em qualquer página de marketing — incluindo homepage, landing pages, páginas de preços, páginas de features ou posts de blog. Também use quando o usuário menciona "CRO," "otimização de taxa de conversão," "essa página não está convertendo," "melhorar conversões," ou "por que essa página não funciona." Para fluxos de signup/registro, veja signup-flow-cro. Para ativação pós-signup, veja onboarding-cro. Para formulários fora de signup, veja form-cro. Para popups/modals, veja popup-cro.
日本語の概要は準備中です。原文の説明を表示しています。
Quando o usuário quer criar ou otimizar uma sequência de email, drip campaign, fluxo de email automatizado ou programa de lifecycle email. Também use quando o usuário mencionar "sequência de email", "drip campaign", "sequência de nutrição", "emails de onboarding", "sequência de boas-vindas", "emails de reengajamento", "automação de email" ou "emails de lifecycle". Para onboarding in-app, veja onboarding-cro.
日本語の概要は準備中です。原文の説明を表示しています。
Controle saída de LLM com regex e gramáticas, garanta geração válida de JSON/XML/código, aplique formatos estruturados e construa fluxos de trabalho multi-etapas com Guidance - framework de geração restrita da Microsoft Research
日本語の概要は準備中です。原文の説明を表示しています。
Fornece orientação para pós-treinamento de LLM com RL usando slime, um framework Megatron+SGLang. Use ao treinar modelos GLM, implementar fluxos de trabalho personalizados de geração de dados, ou precisar de integração estreita com Megatron-LM para escalabilidade em RL.
日本語の概要は準備中です。原文の説明を表示しています。
Agentes de voz representam a fronteira da interação com IA - humanos falando naturalmente com sistemas de IA. O desafio não é apenas reconhecimento e síntese de fala, mas alcançar fluxo de conversa natural com latência inferior a 800ms enquanto se lidam com interrupções, ruído de fundo e nuances emocionais. Esta habilidade cobre duas arquiteturas: fala-para-fala (OpenAI Realtime API, menor latência, mais natural) e pipeline (STT→LLM→TTS, mais controle, mais fácil de depurar). Insight-chave: latência é a restrição. Hu
日本語の概要は準備中です。原文の説明を表示しています。
Create AI-powered social media content for TikTok, Instagram, YouTube, Twitter/X. Generate: images, videos, reels, shorts, thumbnails, captions, hashtags. Tools: FLUX, Veo, Seedance, Wan, Kokoro TTS, Claude for copywriting. Use for: content creators, social media managers, influencers, bra...
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Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, market...
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Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awarene...
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Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search...
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Generate professional AI product photography and commercial images. Models: FLUX, Imagen 3, Grok, Seedream for product shots, lifestyle images, mockups. Capabilities: studio lighting, lifestyle scenes, packaging, e-commerce photos. Use for: e-commerce, Amazon listings, Shopify, marketing, ...
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Prepare and launch LoRA, LoKr, or T-LoRA training through lora-scripts-next (SD-Trainer), Anima-first. Use when the user asks to train a character, style, or concept LoRA, choose parameters or repeats and epochs, start a run, or monitor training on Anima, SD1.5, SDXL, or Flux. Organize and caption the dataset, run dataset-doctor, choose a documented starting preset from image count and VRAM, show one confirmation card, then call the mikazuki API and monitor its log.
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Generate images using AI models — Gemini, DALL·E, Stable Diffusion, Midjourney, Flux, Leonardo, Ideogram, and more. MCP bridge tools are primary; the Design Stack media worker is the fallback for advanced providers. Covers prompt engineering, model selection, size/aspect ratios, style parameters, batch generation, multi-site awareness, and WordPress integration. Use when you need to create hero images, social graphics, product mockups, brand illustrations, or any visual asset for marketing, social media, or e-commerce.
日本語の概要は準備中です。原文の説明を表示しています。
Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.
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Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.
日本語の概要は準備中です。原文の説明を表示しています。
Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration.
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Use when helping users configure LoRA training — select presets, understand parameters, and pick the right settings for their model type. Covers SD1.5, SDXL, SD3, and Flux1 with real-world presets.
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End-to-end genome-scale metabolic modeling from genome sequence to flux predictions. Covers automated reconstruction with CarveMe, model validation with memote, FBA/FVA analysis, and gene essentiality prediction. Use when building metabolic models or predicting metabolic phenotypes from genomic data.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrates the untargeted LC-MS metabolomics pipeline end-to-end (xcms 4.x feature extraction, QC/drift/normalization, confidence-stratified annotation, permutation-validated statistics, background-aware pathway mapping), naming what each stage decides and where it silently fails. Use when running a full LC-MS metabolomics study from raw mzML to enriched pathways and needing the honest handoffs between stages. Each stage defers to its component skill for parameters and traps; for stable-isotope flux (a separate branch, not this untargeted flow) see metabolomics/isotope-tracing.
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Designs and validates quantitative targeted metabolomics assays (MRM/SRM on triple-quadrupole, PRM on high-resolution instruments) to report absolute concentrations. Covers the internal-standard strategy (external cal -> global IS -> standard addition -> stable-isotope-labeled IS), weighted calibration judged by back-calculated %RE not R-squared, ion-ratio quantifier/qualifier confirmation, matrix-effect/recovery characterization, and ICH M10 method validation. Use when quantifying a closed panel of known metabolites with units, building or validating an LC-MS/MS assay, choosing an IS or calibration weighting, or judging whether a reported concentration is trustworthy. For untargeted feature detection see metabolomics/xcms-preprocessing; for group statistics see metabolomics/statistical-analysis; for flux/MID/tracing see metabolomics/isotope-tracing.
日本語の概要は準備中です。原文の説明を表示しています。
Extract dominant-component soil profile variables for EcoSIM grid or template inputs from gSSURGO, with FAO HWSD v2.0 fallback when gSSURGO data are unavailable or incomplete. Use when deriving soil depth, bulk density, field capacity, wilting point, hydraulic conductivity, texture, rock fraction, pH, CEC, or soil organic carbon; or when converting EcoSIM grid NetCDF files to editable Excel workbooks and back.
日本語の概要は準備中です。原文の説明を表示しています。
Read-only consolidated snapshot of an SDD Composy workspace: lifecycle stage, task contracts, trace integrity, loops, fleets, and the next action, without changing any file. Use for 'em que pé está o SDD', 'status do fluxo', 'qual a próxima ação', 'where are we in the workflow'. Do NOT use for git, CI, infrastructure, or other plugins' status, or to change state.
日本語の概要は準備中です。原文の説明を表示しています。