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Image SEO audit — make a site's images discoverable in Google Images and stop them from dragging down Core Web Vitals. Audits alt text quality and coverage, descriptive file names, modern formats (WebP/AVIF), dimensions and compression, responsive srcset, lazy-loading, explicit width/height (CLS), image sitemaps, and ImageObject structured data. Use this skill whenever the user asks about image SEO, alt text, Google Images ranking, image optimization for search, image file size hurting page speed, WebP/AVIF, or image structured data. Trigger on: "image SEO", "alt text", "rank in Google Images", "optimize my images for search", "image alt tags", "WebP", "image compression SEO", "image sitemap", "ImageObject schema", or any image-discoverability / image-performance question. For overall page speed use /seo-analysis; for generating new images use the brand image skills.

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Full SEO audit combining Google Search Console, URL Inspection API, PageSpeed Insights, a technical crawl, keyword research, and metadata, schema, search intent and Core Web Vitals checks. Surfaces quick wins, diagnoses traffic drops and content gaps, and produces an actionable 30-day plan. Use whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, search visibility, technical SEO, URL indexing, or LCP, INP, CLS or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger.

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Cross-model second opinion from Google Gemini — a different AI reviewing the same changes, with deep Google ecosystem knowledge. Three modes: review (pass/fail gate for Google Ads campaigns, SEO metadata, or code), challenge (adversarial stress-test that tries to break your changes), and consult (open Q&A with Gemini on Google Ads strategy, SEO best practices, or implementation questions). Use when the user says "gemini review", "ask gemini", "gemini challenge", "second opinion from gemini", "consult gemini", "stress test with gemini", "what would gemini say", "cross-model review", or "get another opinion". Voice aliases: "gem", "gemini check". Especially useful for Google Ads changes, SEO metadata updates, campaign structure decisions, keyword strategies, and bid/budget changes — Gemini has native Google ecosystem knowledge that complements Claude's analysis.

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XML sitemap audit — find and fix the sitemap problems that quietly waste crawl budget and slow indexing. Discovers the sitemap (robots.txt, /sitemap.xml, sitemap index), validates structure and size limits, and cross-checks the URLs it lists against reality: non-200 / redirected / noindex / canonicalized-away URLs that shouldn't be in a sitemap, plus indexable pages that are missing from it. Reviews lastmod accuracy, sitemap-index organization, and robots.txt reference. Use this skill whenever the user asks about sitemaps, sitemap errors in Search Console, "sitemap couldn't fetch / has errors", crawl budget, pages not getting indexed, or whether their sitemap is clean. Trigger on: "sitemap", "sitemap.xml", "XML sitemap", "sitemap errors", "sitemap audit", "couldn't fetch sitemap", "crawl budget", "pages not indexed sitemap", "sitemap index", "lastmod", "robots.txt sitemap", or any sitemap/crawl-coverage question. For a full-site SEO audit use /seo-analysis; for broken links use /broken-link-checker.

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Use this skill whenever the user asks for a chart, graph, plot, or visualization of data — 'chart this by month', 'show me a breakdown by category', 'visualize the trend'. Covers picking the right chart type for the question being asked, labeling/readability rules, and which plotting library to reach for. Pair with data-analysis for the underlying data prep.

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。

实践认识论：把方案、假说或判断放回实践中检验，按「实践 → 认识 → 再实践」螺旋迭代，并在开始前写明循环终止条件。当你提出了假说要验证、一次尝试失败要复盘再来、发现自己只想不做或只做不想时触发；一次性输出、答案可直接查阅、还没形成假说（先调查）时不触发。 English: Practice-cognition loop. Test a hypothesis or plan in practice, learn from the result, and iterate in a rising spiral with an explicit stop condition. Trigger when a plan needs validation, an attempt failed and must be retried, or you notice thinking without doing (or doing without thinking); skip for one-shot outputs, lookup questions, or before any hypothesis exists.

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Handles git work: atomic commits, rebase, squash, blame, bisect, reflog, and history questions. Use whenever a task needs a commit or a git-history investigation; skip for ordinary code edits.

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。

This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

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。

Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

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。

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.

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 experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis 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。

Use when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.

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 live web and read URLs through the You.com MCP server. Use when you need current information beyond training data: recent releases, docs, pricing, news, or any question where facts may have changed. Two endpoints: keyless basic search at https://api.you.com/mcp?profile=free, or full tools with an API key from https://you.com/platform/api-keys.

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Answers questions about a past agent run from its recording rather than from memory, and replays or forks that run. Use when asked why an earlier run did something, or to reproduce a failure.

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。

Look up official macroeconomic releases, central-bank policy rates, release calendars and FX rates for 22 currencies through the FXMacroData MCP server. Use for questions about CPI, GDP, jobs data, rate decisions, bond yields or what data is due next, when the answer should come from the published number rather than news coverage. Remote server at https://mcp.fxmacrodata.com/mcp; USD works without a key.

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 NVIDIA Parabricks pbrun commands, translate CPU options and check runtime readiness. Use for individual tools, including planning-only questions.

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。

Query Auto Ontology and validate generated SQL, rows, and answers. Use for MCP or REST access, readiness, authentication, conversations, and grounded questions.

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。

Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.

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Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.

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Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory. Do NOT use for: simple questions, short tasks, one-off commands, linting, or code review.

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Orient users to the i4h workflow runtime and route them to the correct stage skill. Use for architecture, support, or where-to-start questions; do not execute a known stage.

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。

Entry skill for Jetson / IGX BSP customization. Asks one core click-to-select setup questionnaire and passes prefilled answers to downstream setup skills.

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DOCA version handling: detect the installed release and validate the four-way match across pkg-config doca-common, applications/VERSION, doca_caps --version, and bfver/mlnx-release on BlueField; reason about NGC tags; look up whether a capability exists on this release; diagnose build-vs-runtime drift. Load it alongside doca-debug when a symptom smells of version skew: "built but nothing on the wire", "undefined reference to a symbol the docs claim exists", "DOCA_ERROR_NOT_SUPPORTED at runtime", "what does latest mean for this tag", or "is my LTS still supported". Once all four sources match, the component's build / run workflow belongs to its own library, service or tool skill. Refuse install / package choice (doca-setup), per-library API questions (matching library skill), DOCA_ERROR_* taxonomy (doca-programming-guide), and the general debug ladder (doca-debug).

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Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.

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。