Results for “content-fetching”

Searches for existing content pages containing a specific block in AEM Edge Delivery Services, reporting URLs with occurrences and variants to help identify test content during development.

Find existing articles on the brand's own blog covering the target keyword or related topics. Extract reusable modules, internal-linking opportunities, and product use cases to anchor the new article in the brand's existing voice.

Analyze and improve the internal link structure of an AEM Edge Delivery Services site by building a link graph from the query index and page content, identifying orphan pages, hub pages, and content silos, and generating specific linking recommendations with suggested anchor text and placement.

Implement and debug network requests, API calls, and data fetching in Expo apps using fetch, React Query, SWR, Expo Router loaders, caching, and offline support.

Rewrites AEM Edge Delivery Services page content for AI search discoverability (Generative Engine Optimization) by analyzing structure, clarity, and factual density.

基于 anchor 论文、topic 关键词或当前 wiki 状态，产出一份排好序的候选论文 shortlist，供用户或上游 skill 决定是否进一步 `/ingest`。当用户问 "接下来该读什么"、"找和这篇相似的论文"、"推荐相关工作"、"这个方向周围有什么" 时触发；`/ingest --discover` 也会内部调用本 skill。本身不 ingest，只提出候选。

为X、LinkedIn、TikTok、YouTube、新闻通讯和跨平台重新利用的多平台活动创建平台原生内容系统。适用于当用户需要社交媒体帖子、帖子串、脚本、内容日历，或一个源资产在多个平台上清晰适配时。

Design loading, skeleton, and progressive content reveal patterns that maintain user confidence and perceived performance.

Diagnoses how to turn a confirmed content topic into effective content, covering format matching, five-dimensional quality assessment, and actionable next steps.

所有联网操作必须通过此 skill 处理，包括：搜索、网页抓取、登录后操作、网络交互等。 触发场景：用户要求搜索信息、查看网页内容、访问需要登录的网站、操作网页界面、抓取社交媒体内容（小红书、微博、推特等）、读取动态渲染页面、以及任何需要真实浏览器环境的网络任务。

Use when you need to fetch records or data from NCBI Entrez databases (PubMed, nucleotide, protein, gene, SRA, etc.) by ID or accession

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Execute this when the user requests code context for a repository, library, or any natural-language code/technology question using DeepWiki, Context7, Exa, git clone, and/or web search+fetch.

Extract warm prospects from competitor and industry post engagers across LinkedIn, Twitter, and blogs

Content Compression