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概要と使いどころ
Modelo da OpenAI que conecta visão e linguagem. Permite classificação de imagens com zero-shot, correspondência imagem-texto e recuperação cross-modal. Treinado em 400M pares imagem-texto. Use para busca de imagens, moderação de conteúdo ou tarefas visão-linguagem sem fine-tuning. Melhor para compreensão geral de imagens.
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。
Buscar automaticamente documentação atualizada de bibliotecas/frameworks para Claude Code via API Context7
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。
Pesquise a documentação da base de código gerada automaticamente para assinaturas de funções, docs de API, definições de classe e comentários de código. Use quando o usuário solicitar "pesquisar docs", "encontrar documentação", "procurar uma função", "verificar a API" ou antes de implementar mudanças para verificar assinaturas e padrões corretos.
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。
Pesquise o histórico de conversas e memória semântica para recordar discussões anteriores, decisões e contexto. Use quando o usuário pedir "pesquise memória", "o que discutimos", "lembra quando", "encontre conversa anterior", "verifique histórico", ou antes de iniciar um trabalho para recordar decisões anteriores.
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。
Execute tarefas de pesquisa autônoma que planejam, buscam, leem e sintetizam informações em relatórios abrangentes.
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。
Converts a job description into a structured candidate-sourcing workflow. Use when the user provides a role and wants candidate criteria, search terms, source recommendations, and a screening process. Must avoid sourcing on sensitive personal attributes.
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。
Compares a group of companies by products, positioning, market focus, and differentiators. Use when the user provides several company records and wants a structured competitive comparison.
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。
Analyzes a dataset of companies or profiles to identify market patterns. Use when the user provides a larger dataset and wants segments, dominant categories, gaps, and emerging patterns.
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。
Designs an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads. Use when the user wants a repeatable lead workflow plan rather than a single source plan.
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。
Use when creating Product Hunt launch carousel images for developer tools, AI tools, open-source projects, GitHub launches, or technical products. Research comparable launches, inspect the project, extract verified proof points, then generate 4-5 launch-ready images with consistent branding, product surfaces, readable copy, and source-grounded claims.
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。
Use when designing, reviewing, or implementing a command-palette / ⌘K layer for an Apple-platform app — keyboard-first global search, ranked and grouped results, native floating panel, and protected destructive commands.
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 clean markdown, text, or targeted chunks from one or more known, publicly accessible webpage URLs via the Tavily CLI. Use when the URLs are already supplied or discovered and the user wants page content rather than more URLs. Do not use to find an unknown page (tavily-search), list a site's URL structure (tavily-map), bulk-extract a site section (tavily-crawl), or retrieve named platform, authenticated, cookie-dependent, or platform-native content (Agent Reach). Can process up to 20 public URLs per request.
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。
MUST USE for GitHub-related operations, including a GitHub URL, repository or code search, Issues, pull requests, Actions, Releases, permissions, and API requests. Use the local GitHub CLI (`gh`).
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。
通过 ClinicalTrials.gov API v2 实时检索官方临床试验注册数据。触发词包括 ClinicalTrials.gov、临床试验、NCT、试验注册、招募状态、phase 1/2/3、RCT lookup、interventional trial、observational study。专注实时单次查询(≤1000 条/请求),适合"某试验最新状态/招募信息/主次要终点"场景。批量历史分析请用 aact-bulk-trials,文献检索用 pubmed-search/europepmc。
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。
Add a new competitor to the AI Visibility Tool Directory — researches the tool, generates data, takes a screenshot, and inserts into the codebase
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。
Run authorized Xiaohongshu browser workflows for login checks, creator preview fill, publish blockers, final posting, search, export, or approved engagement. Prefer native signed-in Chrome; keep Python/CDP for deterministic batch fallback.
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。
Discover and list all URLs on a website, with optional search filtering. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", or "list all pages". Essential when the user knows which site but not which exact page.
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。
Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).
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。
Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.
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。
Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: "PersistentAgentsClient", "persistent a...
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。
Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.
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。
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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。
Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.
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。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
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。