「distribution」の検索結果

Generate editorial calendars for blogs with topic clusters, publishing schedules, material-change reviews, update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars around reader needs, evidence changes, and sustainable publishing capacity. Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".

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 editorial calendars for blogs with topic clusters, publishing schedules, content decay detection, freshness update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars optimized for SEO topic authority and freshness signals based on content priority. Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".

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。

Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for AI-citation SEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".

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。

Create and manage writing personas with NNGroup 4-dimension tone framework (Funny-Serious, Formal-Casual, Respectful-Irreverent, Enthusiastic-Matter-of-fact). Personas define readability targets, sentence length distribution, vocabulary tier, contraction frequency, and summary box label. Used by blog-write and blog-rewrite to enforce consistent voice. Use when user says "persona", "voice", "tone", "writing style", "brand voice", "create persona", "use persona".

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。

Administers the email, chat, meeting and file-sharing platform the organization runs on — tenant and domain configuration, mail authentication and routing, phishing and spam controls, shared mailboxes and distribution groups, external sharing and guest access, permission sprawl in file storage, and retention and legal hold. Use this to configure a tenant, tighten sharing, investigate a mail delivery or phishing problem, or work out who can see a file and why.

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。

Manages laptops, desktops and mobile devices — enrollment, configuration, patching, software distribution, and lost or compromised devices. Use this to set up device management, standardize builds, roll out software or an OS upgrade, handle a lost device, or bring an unmanaged fleet under control.

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。

Builds reporting and self-serve analytics that people actually use — metric trees, dashboard design, distribution, and the discipline that stops dashboards proliferating. Use this to build a dashboard or report, design a metrics framework, set up self-serve analytics, decide what to measure, or diagnose why reporting exists but nobody uses it or trusts 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。

Gets a product listed where buyers and crawlers look — directories, marketplaces, review sites, comparison pages, and aggregators. Use this to plan a submission push, choose which directories are worth the effort, prepare listing assets, build comparison and alternative pages, or manage presence on review platforms.

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。

Get memory system statistics including total count and breakdown by type. When you need to check memory usage or understand memory distribution.

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 validating an existing prognostic risk signature on an external bulk expression cohort with survival outcomes, producing risk scores, Kaplan-Meier curves, risk distribution plots, heatmap, and time-dependent ROC curves. NOT for: model training, feature selection, nomogram construction, calibration analysis, or single-cell data.

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 this skill when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or providers, mentions split payments, revenue sharing, multi-party payments, or similar payment distribution concepts, provides a company URL or business description for a recommendation, builds SaaS that routes money between parties (for example, POS, booking, invoicing — not operational SaaS without payment routing), asks about onboarding or KYC for merchants, sellers, and vendors, mentions connected account Dashboard or responsibility configurations, or asks about payment flows, white-label payments, or embedded payments.

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 evaluating platforms, marketplaces, and networks through a USV-style lens: network effects, defensibility, protocols, openness, and scalable distribution.

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 evaluating startups or growth companies through a Sequoia-style lens: founder quality, market size, product-market fit, distribution, and long-term company building.

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 evaluating crypto narratives, attention rotation, memecoin cycles, Solana-style ecosystem momentum, social distribution, and reflexive retail flows in an Ansem-style crypto market framework.

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 erlang distributed systems including node connectivity, distributed processes, global name registration, distributed supervision, network partitions, and building fault-tolerant multi-node applications on the BEAM VM.

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 Homebrew formula for CLI distribution on macOS and Linux.

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 Chocolatey package for Windows CLI distribution.

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。

Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.

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。

Elite content marketing strategist specializing in AI-powered content creation, omnichannel distribution, SEO optimization, and data-driven performance marketing. Masters modern content tools, social media automation, and conversion optimization with 2024/2025 best practices. Use PROACTIVELY for comprehensive content marketing.

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。

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

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。

Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.

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 packaging an Agentlas agent repo for public GitHub release, Codex plugin submission, Claude adapter distribution, or one-line terminal installation.

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 packaging this meta-agent for public Codex plugin registration, Claude Code installation, GitHub release, one-line terminal install, or open-source distribution.

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 evaluation datasets and supporting documentation for AI systems and agents, covering the scoping interview, difficulty distribution, dataset contract, sample review, and metric and tooling selection. Use when building or reviewing an evaluation set for a conversational agent, assistant, or retrieval-grounded AI system.

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。