「linking」の検索結果

Puts a built website live on a free HTTPS link, or your own .com with no DNS. Use when the user says "put it online", "go live", "make it live", "put this live", "publish my site", "share it with friends", "send my friends a link", "get a link", "make it public", "it only works on localhost" or "get a .com", or asks to deploy or host a site built with an AI tool (Claude Code, Cursor, Codex, Windsurf, Lovable, Bolt, v0, ChatGPT), or mentions DropTheHassle, and has not picked another host. Covers building first, CLI or MCP setup, deploying, the claim link, the live check, linking a server part the user hosts on AWS, Google Cloud, DigitalOcean or their own server with set_backend, and domain search. The agent never spends money. The human pays.

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。

Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".

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 auditing an ACL submission before an ACL Rolling Review cycle deadline, covering long/short paper page budgets, the mandatory Limitations section, Responsible NLP checklist, anonymized PDFs and supplements, preprint declarations, dual-submission rules, resubmission linking, and ARR desk-reject triggers on OpenReview.

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。

Map complete topic clusters for any subject area — hub pages, spoke articles, supporting content, internal linking architecture. Identifies content gaps, priority order, and builds a structured content calendar. Produces topic maps that build genuine topical authority, not random blog posts.

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 detailed, differentiated content briefs at scale. Each brief includes SERP analysis, competing page breakdown, unique angles from real customer language (reviews, Reddit), internal linking plan, and SERP feature targets. Batch mode produces 10-50 briefs in one run. Crushes generic "keyword density" briefs from tools like Surfer or Clearscope.

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。

Assemble an Apple Notes list video ad from a note + end-card JSON — a frame-accurate fake iPhone screen recording of a short list being typed into Apple Notes (character by character, key pops, blinking caret, the note scrolling up as it fills) crossfaded into a checklist end card (the note's picks as ticked rows, real product photos, logo, CTA, in the brand's colours and fonts), with an optional music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand note + end card and gates the paid music call to its own capability. The Apple Notes sibling of render-imessage-chat and render-chatgpt-chat. Use for the apple-notes format.

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 the skill to control and verify the code interface configuration of your model — how Simulink® model elements are represented in the generated C or C++ code. This includes — (1) specifying names, types (storage classes), and placement of variables that represent model elements (for example, making a model parameter tunable as a global extern variable); (2) specifying names, types, and placement of functions that represent model algorithms; (3) selecting the deployment type (Component, Subcomponent, or Automatic); (4) selecting the interface configuration type (data or service interface); (5) linking a shared Embedded Coder dictionary to a model; (6) creating Embedded Coder dictionary entries and setting their properties; (7) for service interface configuration — specifying service interface definitions, including sender, receiver, client, and server services. Items 1 and 2 can be set per element or as a category-wide default. Item 1 applies to GRT and ERT models; the rest to ERT models only.

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Build enhancer-driven gene regulatory networks (eGRNs) by integrating single-cell RNA-seq and ATAC-seq using SCENIC+, CellOracle base GRNs, Pando, FigR, DIRECT-NET, TRIPOD, and scMEGA. Covers the accessibility-defines-enhancers principle, peak-to-gene linking and its cell-composition confound, the paired-vs-unpaired decision, and TF-region-gene eRegulon triplets. Use when analyzing 10x multiome or paired/unpaired scRNA+scATAC to infer cis-regulatory GRNs. For RNA-only regulons see scenic-regulons; for in silico TF perturbation see perturbation-simulation.

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 and download from NCBI Gene Expression Omnibus (GEO) and EMBL-EBI's BioStudies/ArrayExpress mirror. Use when finding expression datasets, navigating SuperSeries vs SubSeries, choosing between series-matrix (submitter-normalized) and raw supplementary files, downloading via GEOparse (Python) or GEOquery (R/Bioconductor), linking GEO to SRA for raw reads, or distinguishing GSE/GSM/GPL/GDS record types. Encodes the SuperSeries trap, the series-matrix normalization-trust caveat, GEOmetadb deprecation, ArrayExpress migration to BioStudies, and processed-vs-raw decision matrix.

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Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.

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Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), TRIBE/HyperTRIBE (ADAR-RBP, A-to-I editing), DART-seq (APOBEC1-YTH for m6A), or Bullseye/SAILOR edit-site detection pipelines. Use when antibody is unavailable or specificity is doubtful, when single-cell RBP profiling is needed (scSTAMP), or when in vivo RBP profiling without UV is preferred.

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Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, identifying enhancer-gene pairs from chromatin alone (without paired RNA), running gene-regulatory inference combining ATAC + RNA, or comparing predicted regulatory contacts against Hi-C/Micro-C ground truth.

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 mentions SwiftUI navigation issues, deep linking problems, state restoration bugs, or navigation architecture review.

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。

Implement SwiftUI navigation patterns including NavigationStack, NavigationSplitView, sheet presentation, tab-based navigation, and deep linking. Use when building push navigation, programmatic routing, multi-column layouts, modal sheets, tab bars, universal links, or custom URL scheme handling.

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 planning or restructuring what pages a site has and how they connect: hierarchy, navigation, URL patterns, breadcrumbs, and internal linking. Not for XML sitemaps, which are in seo-audit.

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。

Content marketing via Shopify blog — SEO content, product education, buying guides, internal linking

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。

When the user wants to optimize for entity recognition, Knowledge Graph, or entity-based SEO. Also use when the user mentions "entity SEO," "entity optimization," "Knowledge Graph," "Knowledge Panel," "entity signals," "brand entity," "entity linking," "entity relationships," or "entity-first content." For structured data, use schema-markup.

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。

Configures environment variables for Power Pages site settings to support ALM across environments. Creates environment variable definitions in Dataverse, guides the user through linking site settings to those variables via the Power Pages Management app, adds the variables to the solution, and generates a deployment-settings.json file with per-stage override values. Use when asked to: "configure environment variables", "add env vars", "set up deployment variables", "make site settings environment-specific", "configure ALM variables", "set up env-specific settings", "add deployment settings", "configure per-environment settings".

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。

Run a comprehensive on-page SEO audit or optimization pass covering title tags, meta descriptions, header structure, content quality, internal links, image optimization, URL hygiene, and on-page schema. Use this skill whenever the user asks to optimize a page, audit on-page SEO, fix titles or meta tags, review header structure, check internal linking, improve a single URL's search performance, or write SEO-friendly copy. Triggers on on-page SEO, page audit, title tag, meta description, H1, header structure, internal links, image alt, URL slug, page optimization, optimize this page, SEO this page. Also triggers for any single-page review where ranking, click-through, or relevance signal quality is the goal, even if the user does not say 'SEO' explicitly.

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。

How to design and run a programmatic SEO program that produces durable traffic instead of penalty-bait. Data source identification, template design, schema patterns, quality control at scale, internal linking architecture, crawl budget management, AEO/GEO for programmatic pages, refresh discipline, and the make-or-break question of whether pSEO is the right answer for your program at all. Triggers on programmatic SEO, pSEO, scaled content, page generation, template SEO, location pages, comparison pages, directory site, listing site, scaled landing pages, programmatic content. Also triggers when a content set is not ranking, has been hit by an algorithm update, or when a team is considering pSEO as a growth lever.

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。

Pre-publish QA framework for content. Brief adherence, voice consistency, fact accuracy, structure and clarity, AI-content audit, SEO and AEO compliance, internal linking and schema validation, QA at scale via sampling, the QA workflow, and the discipline that distinguishes catch-problems QA from checkbox QA. Triggers on editorial QA, content review, pre-publish review, content audit, content QA process, AI-content audit, hallucination check, content sampling, programmatic QA, voice consistency check, brief adherence check. Also triggers when a content team is shipping sloppy work, when AI-co-authored content is reaching publish unaudited, when a QA process burns reviewers out, or when a programmatic SEO set needs sampling discipline. On a voice consistency check, this skill owns checking a draft against an existing voice system at the publish gate; use `brand-voice` when the voice system itself needs defining or documenting.

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。

How to author a content brief that actually guides a writer (human or AI) to produce a piece that ranks, converts, or both. Per-piece editorial brief: target keyword and cluster, search intent, audience and JTBD, heading structure, entity coverage for AEO/GEO, internal linking strategy, success criteria. The middle path between thin briefs (a keyword and a deadline) and thick briefs (a 4-page document nobody reads). Triggers on content brief, brief the writer, brief the article, brief authoring, content brief template, brief audit, per-piece brief, editorial brief, target keyword brief, search intent brief. Also triggers when briefing a human writer or an AI agent on a single content piece.

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 backlink gap domains linking to competitors, not you, scored by script. "who links to our competitors but not us"

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。