「dom」の検索結果

Discuss a domain with the user, research it from real sources, then generate a trusted skill bundle for it - a step-by-step workflow with a flowchart, a domain adapter, a trap fixture, and a smoke eval. Use when the user says "/fable-domain SECTOR", "make a skill for DOMAIN", "add a domain to the fable method", or "give a lesser model Fable's workflow for DOMAIN". The bundle is the deliverable; a workflow without its flowchart, sources, and trap is not done.

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When the user wants to plan or execute a rebrand—domain change, 301 redirects, migration, or announcement. Also use when the user mentions "rebranding," "rebrand," "domain change," "domain migration," "301 redirect," "change domain name," "rebrand announcement," "social media rebrand," "brand launch," or "domain redirect." For domain choice, use domain-selection.

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Get Ahrefs domain overview: Domain Rating, total backlinks, referring domains, organic keywords, estimated monthly traffic, and traffic value. Use when user says "Ahrefs overview", "domain rating", "DR score", "check backlinks", "how strong is this domain", "domain authority", or "check domain in Ahrefs".

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Implement randomization methods for RCTs. Use when user mentions: random assignment, treatment allocation, stratification, blocking, permutation randomization, cluster randomization, randomization balance, misfit handling, re-randomization.

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Generate domain permutations with dnstwist and check DNS resolution to detect typosquatting, homograph phishing, and brand impersonation domains registered against your organization. Use when asked to monitor for lookalike domains, investigate a phishing domain, or assess brand-impersonation risk.

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Content-adaptive wisdom extraction that reads content first, detects which wisdom domains are present, and builds custom sections around them, with five depth levels and mandatory contrarian takes; pulls YouTube via fabric and articles via WebFetch. USE WHEN extract wisdom, analyze video, analyze podcast, extract insights, key takeaways, summarize interview, distill content. NOT FOR static Fabric extract_wisdom pattern (use Fabric).

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Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).

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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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Rigorous, defensible email-spoofability verdict and SPF supply-chain risk analysis computed from published DNS alone. Deepens the record-level SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC fetch recipes in the offensive-osint arsenal (§16.14) with the reasoning that section doesn't do: a priority-ordered composite verdict for whether an attacker can actually land header-From-spoofed mail in an inbox, and by which vector (exact-domain vs subdomain) — grounded in the single most-misunderstood distinction in email security: the envelope MAIL FROM that SPF authenticates vs the visible header From: that only DMARC governs. Explains precisely why SPF -all/~all alone is NOT spoof-proof without DMARC enforcement, and why SPF +all bypasses DMARC even under p=reject pct=100. Covers RFC 7208 §4.6.4's 10-DNS-lookup / 2-void-lookup PermError fail-open condition with a runnable stdlib-only lookup-counter script, plus the SPF-include-takeover supply-chain vector (an attacker re-registering a dead include inherits SPF-pass authority over the victim domain) with strict transient-vs-NXDOMAIN discrimination discipline so a temporary SERVFAIL is never mistaken for a takeover lead. Fully passive: DNS TXT reads only, no mail sent, no RCPT TO probe, no API keys. Use when auditing a domain's real spoofing resistance (not just its published records), explaining to a client why 'we have SPF -all' does not mean they're covered, investigating an SPF PermError or an unusually long include chain, evaluating a dead SPF include as a takeover lead, or writing a defensible spoofability finding for a deliverable.

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Search domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check domain prices, find domain deals, compare registrars, or search for .ai/.com domains.

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Apply DDD tactical patterns when working with domain code, and validate proposed domain models before approval (design mode). Enforces aggregate design, value objects over primitives, entity identity rules, and bounded context boundaries. Use when creating or modifying domain models, designing aggregates, working in the domain layer, or when the user mentions 'domain', 'aggregate', 'value object', 'entity', 'bounded context', or 'DDD'.

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Draft, review, and refactor Reddit comments for any company by providing a domain URL and a Reddit thread. Dynamically extracts product knowledge, approved terminology, voice and tone, and positioning guidelines from the domain before writing. Use this skill whenever the user provides a domain and a Reddit thread and asks to write, draft, review, or refactor a Reddit comment or engagement reply. Trigger on inputs like "Domain: [url] Thread: [url or paste]", "write a Reddit comment for this domain", "draft an engagement for this thread", or any variation where a company URL and a Reddit thread are both provided. Always use this skill — never write Reddit comments for a domain without following this full workflow.

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Structured procedure for expanding attention from focused single-domain mode to panoramic multi-domain awareness. The cognitive transition from "focused attention on one problem" to "unfocused attention encompassing all relevant domains simultaneously." Like Baars' Global Workspace — consciousness as broadcast rather than spotlight. Use after meditation has cleared noise, when a problem spans multiple domains that need to be perceived together, when single-domain analysis keeps missing cross-domain connections, or as the opening move before integrate-gestalt synthesizes what is perceived.

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Use when configuring org-wide platform settings: MFA enforcement, My Domain setup and deployment, session timeout and security settings, password policies, trusted IP ranges (Network Access), and CSP Trusted Sites. Owns these settings as deployable Settings metadata (Security.settings, MyDomain.settings, Company.settings, Language.settings) and the order in which a new org is stood up. Trigger keywords: 'MFA setup', 'My Domain', 'session settings', 'password policy', 'trusted IP ranges', 'CSP trusted sites', 'Security.settings', 'SecuritySettings metadata', 'MyDomainSettings', 'settings-meta.xml', 'enhanced domains', 'deploy org settings', 'new org setup order', 'sessionTimeout enum', 'lockSessionsToIp', 'enableAdminLoginAsAnyUser'. NOT for user-level login restrictions (use user-management), NOT for permission model design (use permission-sets-vs-profiles), NOT for security audit and hardening review (use security/org-hardening-and-baseline-config).

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Audits WordPress plugin or theme PHP code for internationalization (i18n) correctness — text-domain consistency, use of escaped translation helpers (esc_html__, esc_attr__, esc_html_e), correct placeholder helpers (sprintf with translator comments, _n for plurals, _x for context), no variable text-domains, no concatenation inside __() calls, presence of load_plugin_textdomain or load_theme_textdomain, and matching declared Text Domain in the plugin/theme header. Use before plugin/theme release, when reviewing contributor PRs, when adding new strings, when migrating to a new text domain, or when a translator reports issues with the .pot file.

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Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys required.

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Domain routing and boundary guidance for authorized subdomain takeover testing, including dangling CNAME records, NS takeover, and cloud service takeover paths such as S3, Azure, and Heroku. Use when a task belongs to the subdomain takeover domain and needs scope, evidence, pivot, or exit criteria.

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Model software around the business domain using bounded contexts, aggregates, and ubiquitous language. Use when the user mentions "domain modeling", "bounded context", "aggregate root", "ubiquitous language", "anti-corruption layer", "context mapping", "domain events", "strategic design", "the code doesnt match the business", or "how do we split this big system". Also trigger when breaking a monolith into services, defining service boundaries, or aligning code structure with business processes. Covers entities vs value objects, domain events, and context mapping strategies. For architecture layers, see clean-architecture. For complexity, see software-design-philosophy.

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Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain. Use this skill to evaluate affiliate program websites, compare competitor traffic, assess advertiser strength, or understand where an audience comes from. Triggers on: "analyze traffic for [domain]", "how much traffic does [site] get", "compare traffic between [site A] and [site B]", "is [program] worth promoting based on traffic", "traffic analysis", "website analytics for [domain]", "where does [site] get traffic", "check if [advertiser] is legit", "evaluate [program] website health", "SimilarWeb analysis", "traffic sources for [domain]", "how popular is [site]", "website rank", "domain authority check", "compare affiliate program websites".

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Query InterPro for protein domains and families. Use when user asks about protein domains, functional sites, protein families, domain architecture, or motifs. Triggers on "interpro", "protein domain", "domain architecture", "protein family", "functional site", "motif".

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Facilitate a structured conversation to define DDD guardrails for domain design within a repository. Produces a formal ddd-principles.md document that the domain-driven-design atom will use as its override. Use when setting up domain design principles, defining aggregate rules, or when the user says 'setup DDD', 'define domain rules', 'DDD principles', or 'help me define my domain patterns'.

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Domain PrimitivesとAlways-Valid Domain Modelの設計原則に基づき、ドメインモデルの型安全性と不変条件を 保証する設計・実装を支援する。プリミティブ型の濫用を防ぎ、構築時検証・不変性・自己完結性を備えた ドメイン固有の型を設計する。コードレビュー、新規実装、リファクタリング時に使用。 対象言語: Rust, TypeScript, Java。他の言語（Kotlin, Scala, Go, Python等）にも応用可能。 トリガー：「ドメインプリミティブを作りたい」「Always-Validなモデルを設計」「プリミティブ型をラップしたい」 「構築時に検証したい」「無効な状態を型で防ぎたい」「Smart Constructorパターン」等のリクエストで起動。

Meta-mathematical connections, cross-domain synthesis, and the Complex Plane as a navigational tool. Classifies problems by quadrant (Abstract/Embodied x Logic/Creativity), routes them to relevant domains, and traces dependency chains. Use when classifying mathematical problems across domains, navigating the Complex Plane of Experience, finding cross-domain connections, or building multi-domain solution strategies.

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デジタルプロダクト系の専門領域（UI/UX, マーケティング, コピーライティング, ASO, グロース等）の 暗黙知を抽出・言語化・構造化し、他のSkillで使えるエージェント定義と評価基準を生成するスキル。 素人では判断できない「良い/悪い」の基準を、AI が専門家レベルで調査・分析・言語化し、 再利用可能なドメインナレッジとして出力する。 Use when: 評価基準を作りたい、ドメイン知識を抽出したい、専門家の視点を言語化したい、 暗黙知を構造化したい、ベストプラクティスを整理したい。 Triggers: "ドメイン知識", "専門知識", "評価基準", "domain expertise", "expertise extract", "知識抽出", "暗黙知", "ベストプラクティス抽出", "評価基準を作りたい", "専門家の視点", "ドメインナレッジ", "domain knowledge", "expertise builder"