「hub」の検索結果

Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.

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。

NLM PubTator3 实体级关系挖掘原子 skill — 在 PubMed 文献里检索"疾病-药物-基因-化学品-突变-物种-细胞系"的标注与关系三元组。当用户问"BTK 与肺曲霉病的关联文献"、"BTK 抑制剂(MeSH D000077180)在哪些研究被讨论"、"标注这些 PMID 中提到的所有疾病/药物/基因实体"、"ibrutinib 的 MeSH/DrugBank ID"、"voriconazole 与 CYP2C19 药物-基因相互作用"、"BRAF V600E 突变 / rs113488022 检索"、"实体共现 / co-mention / 关系挖掘 / 实体规范化 / NER / annotation / entity normalization / disease-gene association / drug-gene interaction / chemical-disease relation" 时使用。无需 API key,跨平台稳定。**实体级 + 关系级**定位 — 不做综合文献检索(走 pubmed-eutils / europepmc-search)、不做全文段落抽取(走 bioc-fulltext-fetch)、不做证据等级排序(走 medical-evidence-grading)。

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。

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search 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。

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。

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。

Discover ordinary public webpages with LLM-optimized Tavily search results. Use when no specific URL is known and the user needs a quick public-web lookup, articles, recent news, sources, or domain-filtered results. This is the default Tavily leaf for simple public-web discovery. Do not use when the user already supplied the target URL (use tavily-extract), wants URLs under one known site (tavily-map), wants many pages' content (tavily-crawl), needs a full cited synthesis (tavily-research), or needs named platforms, login state, platform-native content, or cross-platform collection (Agent Reach).

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。

飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是 URL 路径模式和 token，而不是域名。

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 PubMed biomedical literature with natural language queries powered by Valyu semantic search. Full-text access, integrate into your AI projects.

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 encountering any bug, test failure, or unexpected behavior, before proposing fixes

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。

Discover and list all URLs on a website without extracting content, via the Tavily CLI. 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", "list all pages", or "site structure". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.

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。

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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。

Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.

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/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image; 1K/2K/4K; use --input-image.

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 a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

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。

中国药品权威数据库查询 — NMPA(国家药监局) + CDE(药品审评中心) + DrugBank(英文名/ATC) + PubChem(化学结构) 多源融合,提供(通用名 ↔ 商品名 ↔ 英文名 ↔ 适应症 ↔ NMPA 批文号 ↔ 上市日期)精确映射。Make sure to use this skill whenever the user mentions 药品名 / 通用名 / 商品名 / NMPA / 国药准字 / 药监局 / CDE / drug brand name / generic name / drug registry / pharmaceutical lookup / drug verification / 药物核验 / 商品名对应 / drug cross-check / drug authority lookup. 在任何 medical / market-sizing / clinical / disease-research 报告生成阶段,**所有药品提及必须先调 lookup_drug() 验证**,严禁 LLM 凭训练记忆拼凑通用名↔商品名↔英文名对应关系。LLM 训练截止后药企会更换商品名、新药持续上市,记忆完全不可信。Iron Law:lookup 返回 None → 调用方必须 raise UnverifiedDrugError,不允许 fallback 到记忆。免费公开数据源,跨平台:Claude Code / Codex / Gemini CLI 三端均可 auto-trigger,实现仅依赖 httpx + beautifulsoup4 标准生态,不绑定任何厂商 SDK。

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。

医学证据等级排序与编排层 skill - evidence grading orchestrator. 当用户请求"证据等级 / GRADE / 证据排序 / 医学证据评估 / 系统评价排序 / 临床证据排序 / 证据金字塔 / 给 PMID 打分 / Practice Guideline 优先 / Cochrane 优先 / 反向证据交叉验证 / evidence grading / quality of evidence / evidence pyramid / GRADE assessment / Cochrane review ranking / clinical evidence ranking"时,**调用本 skill 进行医学证据自动分级,自动选择最佳信息源**。本 skill 是编排层(L2)·不直接打 NCBI/Europe PMC/ClinicalTrials API,而是编排 6 个底层原子 skill(pubmed-eutils / europepmc-search / clinical-trials-v2 / aact-bulk-trials / bioc-fulltext-fetch / pubtator-entity-search)的召回结果,按证据金字塔(指南 > Meta > RCT > Cohort > Case-Control > Case Report)做 GRADE A/B/C/D 自动评级,自动剔除 editorial/letter/comment。优先使用 BioMCP MCP server 做 fan-out(genomoncology/biomcp);无 BioMCP 时走自建 slow-path 兜底。跨平台无锁(Claude Code / Codex / Gemini 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。

医学证据等级排序与编排层 skill。当用户请求"证据等级 / GRADE / 证据排序 / 医学证据评估 / evidence grading / quality of evidence / 系统评价排序 / 临床证据排序 / 证据金字塔"时触发。本 skill 不直接调用 NCBI/Europe PMC/ClinicalTrials API,而是编排 6 个底层原子 skill(pubmed-eutils / europepmc-search / clinical-trials-v2 / aact-bulk-trials / bioc-fulltext-fetch / pubtator-entity-search)的召回结果,按 ChatGPT 推荐的证据金字塔(指南 > Meta > RCT > Cohort > Case-Control > Case Report)做 GRADE 自动评级,自动剔除 editorial / letter / comment。优先使用 BioMCP MCP server 做 fan-out(genomoncology/biomcp),无 BioMCP 时走自建 slow-path 兜底。

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 when an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author for that.

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 engineering principles for making interfaces feel polished. Use when building UI components, reviewing frontend code, implementing animations, hover states, shadows, borders, typography, micro-interactions, enter/exit animations, or any visual detail work. Triggers on UI polish, design details, "make it feel better", "feels off", stagger animations, border radius, optical alignment, font smoothing, tabular numbers, image outlines, box shadows.

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 this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering 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。