「exa」の検索結果

Comprehensive SEO analysis for any website, page, business, or topic. Full site audits, SEO checks, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, content quality (E-E-A-T), image optimization, sitemap analysis, GEO for AI Overviews/ChatGPT/Perplexity, and SEO best-practice planning. Industry detection for SaaS, e-commerce, local, publishers, agencies. Triggers on: SEO, audit, full SEO check, SEO best practices, optimize my site, ranking, organic search, schema, Core Web Vitals, sitemap, E-E-A-T, AI Overviews, GEO, technical SEO, content quality, page speed, structured data.

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Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

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Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", "google api setup", "real CWV data", "impressions", "clicks", "CTR", "position data", "LCP", "INP", "CLS", "FCP", "TTFB", or "Lighthouse scores".

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Turn drafted legal docs (privacy policy, terms) into hosted pages and set the App Store Connect Privacy Policy / Support / Marketing URLs via the ASC REST API. Use at Phase 6 / submission, after legal drafts exist. The App Privacy "nutrition label" stays manual (Apple exposes no API) — this prints the exact answers to click.

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This packages provides C++ header files for developers wishing to create R packages that processes BAM files. ompBAM automates file access, memory management, and handling of multiple threads 'behind the scenes', so developers can focus on creating domain-specific functionality. The included vignette contains detailed documentation of this API, including quick-start instructions to create a new ompBAM-based package, and step-by-step explanation of the functionality behind the example packaged in

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The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules fr

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The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, an

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Precise knowledge on the binding sites of an RNA-binding protein (RBP) is key to understand (post-) transcriptional regulatory processes. Here we present a workflow that describes how exact binding sites can be defined from iCLIP data. The package provides functions for binding site definition and result visualization. For details please see the vignette.

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Analyze the photograph uploaded by the user, deconstruct its visual evidence, abstract and distill the essential relationships, then reconstruct them as a new nonliteral lower-panel composition guided by 19 bundled references. Use for CLEAN upper-photo/lower-abstraction editorial artworks with a number, date, and short phrase in the lower panel. This is abstraction and reconstruction, never style conversion or a miniature redraw. Preserve the exact user-uploaded photograph unchanged above.

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已有功能的需求变更闭环（门禁式七步）。触发硬条件：要改的功能已经实现并跑起来了。当用户说"改需求""需求变更""调整交互""改功能""重构流程"，或改动容易散到多个文件、碰到鉴权/存储/配置/权限、需要可靠验证 + 回滚方案时使用。流程：锁 scope 写 change brief → 从代码确认当前行为（不靠记忆和假设）→ 影响面与风险评估 + 回滚计划 → 提出新设计等用户批准（**未获批准绝不动代码**）→ 小而局部的 diff → 跑固定回归清单 → 更新文档和决策日志。产出：change brief + 代码 diff + 回归记录 + decision log。不适用于：全新功能从零做（走 issue-pool → page-solution-design（有界面时）→ backend-logic-design（有规则需讨论时）→ prd-test-writer）、只改视觉样式不动任何逻辑（按已有界面直接调整）、新想法还没定要不要做（先用 issue-pool 入池）、写 PRD/测试用例（用 prd-test-writer）、提交推送发版（用 git-push）。注意：本 skill 的七步流程通用于任何项目，但 scripts/impact_scan.sh 与 references/chrome-extension-regression-example.md 是 Chrome 扩展示例；通用回归使用 references/regression-checklist.md，按项目实际选择检查。

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Expert knowledge for Azure Oracle development including troubleshooting, security, and integrations & coding patterns. Use when configuring Oracle TDE with Azure Key Vault, fixing Oracle@Azure issues, or exporting Exadata logs to Azure Monitor/Sentinel, and other Azure Oracle related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), SAP HANA on Azure Large Instances (use azure-sap).

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Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing AKS/microservices, hybrid/Arc, SAP or mainframe migrations, IoT/Edge, or mission-critical BCDR, and other Azure Architecture related development tasks.

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Build a SOUL from an X handle - read a wide sample of a public X account, then draft SOUL.md (identity, worldview, opinions), STYLE.md (voice), and examples so every skill speaks in that voice.

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Helps the user come up with free lead magnets or hooks to offer in cold emails. Asks about their business, what they can legally give away, and what would be genuinely valuable to their ICP. Returns 5-10 concrete offer ideas with example CTA phrasings. Use when the user says their campaign "needs a hook", "needs an offer", "what can I give away", or when ICP onboarding flagged a missing lead magnet.

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Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

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Produces a copy-ready clause about a role a company is currently hiring for, filtered by language the client cares about (for example "cold call", "outbound prospecting", "Salesforce"). Triggers on "they're hiring", "job posting language", "who is hiring SDRs", "companies hiring for X", "find the hiring signal", "what roles are they hiring for", "job description mentions". Outputs job_posting_line_safe, one lowercase clause that slots into "Saw {{job_posting_line_safe}}."

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Amazon PPC campaign builder and optimizer for sellers. Two modes: (A) Build — design a complete campaign structure from scratch with keyword groupings, bid calculations, and negative keyword lists, (B) Optimize — audit existing campaigns using search term reports, identify keyword funnel opportunities, calculate bid adjustments, and generate a week-by-week action plan. Integrates with amazon-keyword-research for keyword input. No API key required. Use when: (1) setting up Amazon PPC campaigns for a new product, (2) auditing existing campaign performance and ACoS, (3) optimizing keyword bids and negative keywords, (4) building Auto/Manual/Exact campaign structures, (5) analyzing search term reports for opportunities, (6) calculating break-even ACoS and target ACoS, (7) scaling profitable campaigns to Sponsored Brands or Display.

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Use when you need to define exactly who the buyer is, what they want, what they’ve tried, and what’s driving their decisions. Trigger on "target audience", "ideal client", "who is this for", "avatar", "customer profile".

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。

Calibrate a reviewer persona with few-shot rubric examples so skepticism stays consistent and doesn't drift lenient over long runs.

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 the exact commit that introduced a bug. Use when something worked before and broke, and you don't know which change did it.

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。

Draft, audit, or minimally revise English- or Chinese-language academic prose to reduce formulaic, vacuous, mechanically repetitive, or process-leaking language while preserving claims, evidence strength, logical relations, manuscript-wide terminology identity, document-level pattern variation, and scholarly register. Use for papers, abstracts, grants, cover letters, and reviewer responses when the user asks to de-AI, humanize, audit AI-like phrasing, or rewrite text without changing meaning. English is primary; Chinese is supported. Not for detector evasion, policy circumvention, pure translation, non-academic copy, or adding facts, citations, examples, or author experiences that the source does not contain.

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Common design patterns with Java examples (Factory, Builder, Strategy, Observer, Decorator, etc.). Use when user asks "implement pattern", "use factory", "strategy pattern", or when designing extensible components.

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SOLID principles checklist with Java examples. Use when a class has too many responsibilities, an abstraction leaks, or a dependency points the wrong way, and when the user asks about Single Responsibility, Open/Closed, Liskov, Interface Segregation or Dependency Inversion. For naming, duplication and method length, use clean-code instead.

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Use when the user asks about camera movements, shot types, or how to describe camera behavior in a Higgsfield prompt. Contains all named camera controls with descriptions, best use cases, and example prompt phrases.

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。