「providers」の検索結果

Capability-based multi-tool matrix for research, note-taking, document authoring, and publishing. Agents compose providers (CLI-Anything harnesses, public CLIs, Python libs, native binaries, cloud APIs) per capability.

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。

Organizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST API or configuring its local or cloud AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral.

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。

Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.

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。

Replace the manual commit-by-commit classification step in `breeze release-management prepare-provider-documentation` with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by inspecting the actual diff, scope multi-provider PRs to the current provider's slice, ask the release manager when uncertain, and apply version bumps + changelog entries. Use during the regular provider release cycle as an alternative to the interactive breeze prompts.

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。

Upgrade the pinned Flask-AppBuilder (FAB) dependency in the Apache Airflow FAB provider (`providers/fab/`). Bumps the exact `flask-appbuilder==` pin and its mirror constant, regenerates `uv.lock`, drives the `test_fab_alignment.py` drift tripwire, reviews the vendored security-manager `override.py` against the new upstream FAB, and conditionally re-vendors static assets / DB migrations. Use when asked to "upgrade FAB", "bump flask-appbuilder", or move the FAB provider to a newer Flask-AppBuilder release.

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。

Configure, manage, and use DeepTutor through its CLI, including capabilities, knowledge bases, partners, memory, sessions, notebooks, providers, skills, and the server or Web app.

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。

OpenMAIC assistant for setting up, generating, and extending OpenMAIC. Use when the user wants to use OpenMAIC, generate a multi-agent interactive classroom, or build on / extend / customize OpenMAIC and its @openmaic/* SDK (secondary development, 二开) — covers Live Demo or local setup, startup modes, provider keys, classroom generation, and secondary development (forking, providers/storage/themes, routes, or the renderer/editor).

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。

Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.

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。

Guide for using the Microsoft Fluent UI Blazor component library (Microsoft.FluentUI.AspNetCore.Components NuGet package) in Blazor applications. Use this when the user is building a Blazor app with Fluent UI components, setting up the library, using FluentUI components like FluentButton, FluentDataGrid, FluentDialog, FluentToast, FluentNavMenu, FluentTextField, FluentSelect, FluentAutocomplete, FluentDesignTheme, or any component prefixed with "Fluent". Also use when troubleshooting missing providers, JS interop issues, or theming.

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。

The single ROUTER for every data need. Load this skill BEFORE any backtest, data-fetch, or research task to pick the best available source/tool, honour auth (env) requirements, and avoid ban-risk providers.

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。

Find people, companies, posts, jobs, service providers and groups on LinkedIn with the Curviate CLI. Covers `search people|companies|posts|jobs|services|groups`, running a pasted LinkedIn search URL directly, the `group` read commands, pagination with `--all`, and the filter traps that silently return unfiltered results. Use when sourcing prospects or candidates, qualifying companies, finding posts or job postings to engage with, or resolving a group.

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。

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

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。

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.

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。

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

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。

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

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 the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.

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。

The meta skill. Turn any raw feature into a properly-skilled, tested, resolvable unit of agent capability. Idempotent: running on an existing skill improves it (bug fix, new input, quality pass) instead of starting from scratch. Every skill declares an EVAL CONTRACT (its goal + skill-specific dimensions + hard-fails) so the cross-modal eval judges THIS skill's real purpose, not generic slop. Cross-modal eval runs BEFORE tests: 3 frontier models from different providers critique the output against the contract, you iterate to quality, THEN write/update tests that lock in the proven-good behavior. NO-REGRESSION LAW: any edit to a skill must score >= the previous iteration's eval — forward only, never back. For skills that back a scheduled job, an edit MUST re-run a representative task and eval it before shipping.

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 the user needs help configuring Crush — writing crushrc (the Bash config format) or crush.json, setting up providers, models, LSPs, MCP servers, hooks, skills, permissions, or changing Crush behavior.

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。

Build complete transactional email systems: React Email templates, provider integration (Resend, Postmark, SendGrid, AWS SES), preview server, i18n support, dark mode, spam optimization, analytics tracking. Use when adding transactional email to a new product, migrating between email providers, refactoring legacy email templates for accessibility, or adding internationalization to existing templates.

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 a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.

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。

Make the desktop's model provider fail on demand (connection refused, DNS not found, socket reset, 429, 5xx, 401, 402, stalled or cut stream) with a local fault server and test providers. Use when reproducing or designing model error and retry states without a real outage.

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。

Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.

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。

Answer questions about the Paseo product and app, including setup, configuration, connectivity, providers, workspaces, updates, logs, and troubleshooting. Use when a user inside Paseo asks how Paseo works, how to configure it, or why something is broken; use the paseo skill instead to operate agents and workspaces through MCP or the CLI.

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。

SolidJS renderer for json-render. Use when building @json-render/solid catalogs/registries, wiring Renderer providers, implementing bindings/actions, or troubleshooting Solid-specific reactivity 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。