「dom」の検索結果

Free domain research and availability checking. No API keys or credentials required. Uses RDAP (1195+ TLDs) with whois CLI fallback for universal coverage. Checks if domains are available, searches keywords across TLDs, performs WHOIS/RDAP lookups, checks expiry dates, and finds nameservers. Use when the agent needs to: check if a domain is available, search for domains, find who owns a domain, check domain expiration, get nameservers, bulk check domains, or do any domain research. Triggers on: 'check domain', 'is domain available', 'search domains', 'domain availability', 'who owns this domain', 'whois', 'domain expiry', 'when does domain expire', 'nameservers for', 'domain research', 'find domains for', 'domain ideas', 'bulk domain check'.

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。

Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.

When the user wants to choose an SEO-friendly domain for a new site—brand vs keyword domain, TLD selection, or domain best practices. Also use when the user mentions "domain choice," "pick domain," "SEO-friendly domain," "brand domain," "EMD," "PMD," "exact match domain," "partial match domain," "TLD," ".ai domain," ".com vs .io," "domain length," "domain history," or "defensive domain registration." For migration, use rebranding-strategy.

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。

Add a custom domain to a Temps project and provision an automatic SSL/TLS certificate via Let's Encrypt, driven entirely from the `@temps-sdk/cli` CLI. Handles subdomains, apex domains, HTTP-01 and DNS-01 challenges, and wildcard domains. Use when the user wants to: (1) Add a custom domain to their Temps app, (2) Set up HTTPS/SSL for a deployment, (3) Point their own domain at a Temps project, (4) Add a wildcard domain, (5) Configure DNS for Temps. Triggers: "add custom domain", "point my domain at temps", "set up ssl", "https for my app", "wildcard domain", "add domain to project".

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。

Fix "Fastly error: unknown domain" 500 errors when custom domains return "Domain Not Found" despite being created with domain-v1 CLI. Use when: (1) fastly domain-v1 create succeeds but domain returns 500, (2) Domain shows activated:false in API response, (3) Classic domain API returns "deprecated" error, (4) Custom domain works on edgecompute.app but not on your domain. Covers Fastly Compute domain setup post-September 2025.

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。

ドメインのサブドメイン、SSL証明書、登録情報、DNSレコードを調べるスキル。複数ドメインの一括調査や登録状況の推定に対応し、結果をJSONで返します。

• 公開ログからサブドメインを探したいとき
• SSL証明書の期限を確認したいとき
• 登録情報やDNS設定を調べたいとき

Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters).

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 decide domain structure for multiple products or brands—subfolder vs subdomain vs independent domain. Also use when the user mentions "subfolder vs subdomain," "subdirectory vs subdomain," "multiple products domain," "multiple websites," "brand architecture," "branded house," "house of brands," "where to host product," "domain structure," or "hub-spoke domain." For brand SERP, use multi-domain-brand-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。

When the user wants to optimize brand search for a company with multiple domains (e.g. parent company.com vs product.ai). Ensure the parent/company domain ranks first for brand queries. Also use when the user mentions "brand search," "multi-domain SEO," "company domain first," "parent vs product domain," "hub-spoke domain," "brand SERP control," or "differentiate company and product domains." For domain structure, use domain-architecture.

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。

Research domain WHOIS data and check marketplace listings. Use when the user says "domain lookup", "check domain", "WHOIS", "domain availability", "buy domain", "domain research", "who owns this domain", "domain marketplace", or asks about researching or acquiring a domain name.

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。

Facilitate DDD domain modeling sessions via EventStorming conversation and DML (Domain Modeling Language). Use whenever the user wants to model a business domain by discovering domain events, commands, aggregates, policies, read models, and bounded contexts through dialogue. Produces incrementally-built DML as the primary artifact, plus a Markdown session report. Also invoke for refining existing DML, mapping out a new feature's domain model, or when the user says "ドメインモデリングしたい", "イベントストーミング", "DDDで整理したい", "DMLを育てたい".

When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability" method. Combines Vercel CLI, whois, Domainr, Namecheap, and agent-browser, each for what it reliably does. Workflow: budget → brainstorm → availability check → whois cross-check → price → aftermarket sweep (plus liveness probe and drop-watch) → bucket → negotiate → trademark + socials → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."

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。

Fix wildcard subdomain routing for Fastly Compute@Edge services when subdomains resolve but return 500 "Domain Not Found" or empty responses. Use when: (1) TLS subscription "issued" but edge serves default certificate (CN=j.sni-644-default), (2) Fastly domain-v1 create succeeds but subdomain returns 500, (3) Static publisher/PublisherServer returns empty content for subdomain requests, (4) DNS wildcard CNAME resolves to wrong target. Covers TLS configuration SNI endpoint selection (x.sni vs j.sni vs w.sni), DNS trailing dot issues, Fastly domain-v1 activation, and reading from KV store directly when PublisherServer fails for subdomains.

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。

Expert guidance for Domain-Driven Design architecture and implementation. Use when designing complex business systems, defining bounded contexts, structuring domain models, choosing between modular monolith vs microservices, implementing aggregates/entities/value objects, or when users mention "DDD", "domain-driven design", "bounded context", "aggregate", "domain model", "ubiquitous language", "event storming", "context mapping", "domain events", "anemic domain model", strategic design, tactical patterns, or domain modeling. Helps make architectural decisions, identify subdomains, design aggregates, and avoid common DDD pitfalls.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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, manage, and optimize a domain portfolio. Use this skill for DNS architecture decisions, redirect strategies, registrar choice, parking unused domains, multi-site setups, and domain consolidation or split planning. Triggers on DNS, domain, registrar, redirect, parking, subdomain, apex, www vs non-www, multi-site, portfolio, hreflang setup, domain migration. Also triggers when planning a new site that needs domain decisions made before launch.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。

Passive domain reconnaissance using Python stdlib. Use this skill for subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys required. Triggers on requests like "find subdomains", "check ssl cert", "whois lookup", "is this domain available", "bulk check these domains".

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。

Maps business domains and suggests service boundaries in any codebase using DDD Strategic Design. Use when asking "what are the domains in this codebase?", "where should I draw service boundaries?", "identify bounded contexts", "classify subdomains", "DDD analysis", or analyzing domain cohesion. Do NOT use for grouping existing components into domains (use domain-identification-grouping) or dependency analysis (use coupling-analysis).

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。

Trustpilot company profile lookup on trustpilot.com — input a company domain (e.g. apple.com, shopify.com, shopwagandtail.com) and extract company metadata: official display name, businessUnitId, TrustScore (1-5), star rating, total review count, last-12-months review count, primary category and all categories, verification flags (verifiedByGoogle, verifiedPaymentMethod, verifiedUserIdentity), claimed/closed status, website URL, contact info (email, phone, country, city, address, zip), profile image, and optional reply behavior metrics (averageDaysToReply, replyPercentage, negativeReviewsWithRepliesCount, companyUsesAIResponses). Detects company-not-found and returns isCompanyFound=false with the searched domain. Use when user mentions Trustpilot company info, Trustpilot TrustScore, look up Trustpilot rating, check Trustpilot stars, Trustpilot business profile, Trustpilot review count, Trustpilot company lookup, Trustpilot verification status, Trustpilot reply percentage, Trustpilot AI responses, business unit ID Trustpilot, get company rating from Trustpilot, scrape Trustpilot company, batch enrich domains with Trustpilot, bulk company info Trustpilot, fast domain enrichment with TrustScore, Trustpilot company metadata, Trustpilot brand monitoring, competitor TrustScore comparison, trustpilot.com domain enrichment, trustpilot company profile, trustpilot domain check, trustpilot business listing, check if company is on Trustpilot, Trustpilot category lookup, company contact info from Trustpilot. Also applies to lead-list enrichment with reputation scores, supplier vetting, agency or KOL vetting via review reputation, aggregator sites that need TrustScores for many domains, due-diligence workflows, and pre-outreach reputation checks.

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。

Hunt client-side DOM vulnerabilities — DOM Clobbering (overwrite JS globals via HTML injection), PostMessage hijacking (missing origin check), Service Worker abuse (intercept requests from same-origin script), CSS Injection/Exfiltration (attribute selectors → token char-by-char via OOB), client-side template injection, dangerouslySetInnerHTML. Grounded in named public research: Gareth Heyes / PortSwigger DOM-clobbering + DOM-Invader, Michał Bentkowski DOMPurify clobbering bypasses, jQuery htmlPrefilter XSS (CVE-2020-11022 / CVE-2020-11023), d0nut CSS-exfil research. Use when hunting DOM-XSS, client-side auth bypass, or token exfiltration without server-side interaction.

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。

Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.

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。