1.5万 件 ・ 関連度順
概要と使いどころ
Create an implementation plan and a GitHub Issue based on the task description provided as an argument. Use this when the user supplies a natural-language task description (not an issue number) and wants a new implementation-ready Issue. If the input is an existing issue number, use create-issue-from-issue-number (re-analyze) or update-issue (reflect comments) instead.
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 the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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 starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree 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。
Project-level workflow for turning GitHub repositories, URLs, local product materials, or markdown drafts into WeChat Official Account articles and draft-box submissions. Use when the user asks to write, adapt, illustrate, verify, or publish a WeChat/公众号 article, especially from a GitHub repo or existing technical/product material.
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。
Research-grounded typography for any text-bearing surface — web, PDF, email, documents. GENERATIVE: apply correct line length, font sizing, contrast, dark mode, mobile, and Japanese rules from the start when building any UI, page, layout, or document. REVIEW: audit existing CSS/HTML/templates for typography violations. Use this skill whenever you are writing CSS that touches font-size, line-height, max-width, color, or font-family. Use it when building any frontend component, page, or layout — even if the user doesn't mention typography. Use it when reviewing any rendered output for readability. Use it when generating PDFs, emails, or any formatted document. If text will be read by a human, this skill applies.
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 ordinary public-web information tasks to the correct Tavily CLI operation. Use when the task concerns publicly accessible webpages and needs web discovery, clean extraction, URL mapping, same-site crawling, or public-web-only research, but the exact Tavily operation is not yet clear or several operations must be sequenced. Prefer the specific leaf skill when intent is clear: tavily-search for discovery without a URL, tavily-extract for known URLs, tavily-map for URL/site-structure discovery, tavily-crawl for content from many pages on one site, tavily-research for cited multi-source synthesis, and tavily-dynamic-search for programmatic filtering with context isolation. Do not use for named social/community/media/career/code platforms, login or cookie-dependent content, platform-native discussions, or cross-platform collection; use Agent Reach there. Do not use for local files, Git operations, deployments, or ordinary code editing.
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。
Record browser or Web UI interaction demos as optimized GIFs using the available built-in browser, state-based frame capture, and deterministic encoding, then publish to a dedicated assets branch when the task includes attaching the GIF to a pull request. Use when asked to make, record, or generate a GIF that demonstrates a browser workflow, and for every pull request that changes product-user-visible GUI behavior, which MUST include a GIF recorded from the pull request's real server and model flow.
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。
Retrieves scientific papers from PubMed and creates plain-language research summaries. Use when users ask about medical research, scientific studies, clinical trials, disease treatments, or want to understand recent scientific literature on any biomedical topic.
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。
Audit and safely clean local project repositories or workspaces with excessive generated files, old project residue, dirty Git status, stale worktrees, build caches, duplicate nested projects, confusing roots, or agent context/token waste. Use when the user asks to organize a repo, remove useless files, classify valid project files, clean untracked/deleted files, reduce disk usage, migrate from an old repo layout to a canonical project, or prepare a repository for future Codex/agent work.
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 task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
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。
Mid-run failure recovery for disease-market-sizing-orchestration. Inspects .cache/<slug>/ to determine which phase last completed and which phase to run next. Use when orchestration was interrupted and user wants to continue without restarting from phase 1.
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。
Convert documents to Markdown using Microsoft's MarkItDown CLI (`markitdown`). Supports PDF, Word, PowerPoint, Excel, images (OCR), audio (transcription), HTML, YouTube, and URLs. Use when a user wants to convert a file or URL to Markdown, extract text from PDFs/images, transcribe audio/video, or batch-convert documents.
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 Lingzao creator-content tools for Xiaohongshu/XHS, Douyin, and WeChat official-account public content. Lingzao supports XHS SEO, Xiaohongshu account analysis, benchmark account discovery, viral note breakdown, keyword research, one-stop content packages from keyword/link/image/inspiration material, title and cover optimization, hand-drawn route-map cards, city food maps, travel itinerary maps, life checklist maps, workflow manual maps, creator content workflow, note search, creator search, profile lookup, recent posts, deep profile copy/subtitle analysis, note/article detail, post comments, article stats, related articles, short-video copy extraction, and prompt-based creator image generation.
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 comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.
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 writing, moving, reviewing, or auditing documentation in the deepseek-harness repo — choosing hierarchy and detail, separating tutorials from references, checking tutorial progression, trimming doc slop, responding to a verify-doc-budgets failure, or requests like "improve the docs", "audit the docs", "where should this be documented", or "this doc is too long".
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 working in the deepseek-harness repo to find non-obvious simplification candidates, write proposed Agent Notes or inline TODO/FIXME/XXX notes, audit or coalesce superseded Agent Notes, or fold worthwhile simplification ideas from another PR; especially for dead, duplicated, speculative, over-built, added-then-removed, or hand-rolled-where-a-dependency-exists surfaces.
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 publishing, updating, moving, or removing DeepSeek Harness documentation website pages; editing website/docs.ts mappings or navigation; diagnosing a page missing from the VitePress site; fixing projected documentation links; or running the docs:dev, docs:check, and doc-sync workflow after website-content 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。
Phase 2 of disease-market-sizing-orchestration. Discovers disease-specific stratification dimensions by citing guideline sections from sources/guidelines/. ALWAYS uses cite-based discovery — NEVER built-in stratification templates. Output: .cache/<slug>/staging.json. Use AFTER contract-elicitor and AFTER A1' guidelines fetch.
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。
AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
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。
给定 PMID/PMCID 取结构化全文（NLM BioC XML/JSON）。封装 BioC PubMed（标题+摘要）和 BioC PMC OA（开放获取全文）端点，输出按章节切分的段落、表格上下文、RAG 友好 chunk，适合大批量入向量库。Fetches structured fulltext from NLM BioC API for PMID/PMCID, outputs section-segmented paragraphs and RAG-ready chunks. 触发词：全文抽取 / BioC / RAG 入库 / 文献全文 / PMC 开放获取 / structured fulltext / 段落抽取 / 表格抽取 / chunking / fulltext to vector store / paragraph extraction.
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。
Shared fixture from the repository.
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 Markdown to styled HTML with WeChat-compatible themes. Supports code highlighting, math, Mermaid (rendered to PNG via headless Chrome), PlantUML, footnotes, alerts, infographics, and optional bottom citations for external links. Use when user asks for "markdown to html", "convert md to html", "md 转 html", "微信外链转底部引用", or needs styled HTML output from markdown.
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 aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
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。