1.2万 件 ・ 関連度順
概要と使いどころ
Free meta-search via SearXNG — aggregates results from 70+ search engines. Self-hosted or use a public instance. No API key needed. Falls back automatically when the web search toolset is unavailable.
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。
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image 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。
Plan, set up, and monitor a multi-agent video production pipeline backed by Hermes Kanban. Use when the user wants to make ANY video — narrative film, product/marketing, music video, explainer, ASCII/terminal art, abstract/generative loop, comic, 3D, real-time/installation — and the work warrants decomposition into specialized profiles (writer, designer, animator, renderer, voice, editor, etc.) coordinated through a kanban board. Performs adaptive discovery to scope the brief, designs an appropriate team for the requested style, generates the setup script that creates Hermes profiles + initial kanban task, then helps monitor execution and intervene when tasks stall or fail. Routes scenes to whichever Hermes rendering / audio / design skill fits each beat (`ascii-video`, `manim-video`, `p5js`, `comfyui`, `touchdesigner-mcp`, `blender-mcp`, `pixel-art`, `baoyu-comic`, `claude-design`, `excalidraw`, `songsee`, `heartmula`, …) plus external APIs for TTS, image-gen, and image-to-video as needed.
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。
Persistent AI companion with long-term memory, project context awareness, and multi-session continuity across any LLM.
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。
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
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。
Control Philips Hue lights, scenes, rooms via OpenHue 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。
Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.
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。
Download media (images/videos/GIFs/audio) from Twitter/X using gallery-dl. Supports single tweet URLs, user timelines, date filtering, post count limiting, retweet filtering, video quality selection, and various media types. Use when users want to download media from Twitter/X accounts with proxy support (HTTP/SOCKS4/SOCKS5) and cookie authentication. Supports downloading tweet text with links alongside media.
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。
Review a module or recent change for correctness, maintainability, and risk
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 and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
Triage GitHub issues through gh and a label-based state machine. Use when the user intentionally wants GitHub issue triage, incoming bug or feature review, issue workflow labels, needs-info follow-up, or ready-for-agent briefs.
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。
Break a plan/PRD into independent vertical-slice Beads issues with explicit dependencies.
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 a conversational QA session where the user reports bugs or issues, and file durable Beads issues using project domain language. Use when the user wants to report bugs, do QA, file issues conversationally, or mentions a QA session.
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。
Register a new sub-repo in the knowledge base.
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。
Synthesize current context into a PRD and file it as a Beads feature/epic issue.
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。
Phase 3 of the Forge pipeline. Execute the plan's Beads tasks with red-green-refactor TDD, committing per checkpoint and pausing at each natural stopping point so the user can run a live demo or test and see the work themselves. Use when starting /forge-implement or the implement step of /forgemaster.
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 codebase from knowledge files. Use when the user runs /ask or asks a domain/knowledge question about the repos.
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。
Auto-generate knowledge YAML from the codebase. Use when the user runs /sync-knowledge or wants knowledge files refreshed.
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。
Route a task by complexity and run the gated Forge pipeline (research → plan → implement → ship). Use when the user runs /forgemaster or wants the full guided feature pipeline.
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。
Produce a higher-level architecture and context map for unfamiliar code. Use when you need to understand how a file, module, feature, or issue fits into the bigger picture, including relevant modules, callers, callees, dependencies, and next context.
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。
Surface architectural friction and propose deepening opportunities that improve testability and AI-navigability. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase easier for agents to navigate.
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 the full Forge pipeline unattended: each phase is reviewed by a fresh evaluator subagent, the findings feed back, and the run advances itself. Use when the user runs /forgemaster-auto or wants a feature built end to end without approval gates.
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。
Search, create, and manage notes in an explicit Obsidian vault with title-case filenames, wikilinks, index notes, backlinks, and safe vault-root confirmation.
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。
Generate structured weekly status reports covering initiatives, progress, blockers, risks, and KPIs.
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。