「recommendations」の検索結果

Generate detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, evidence-backed section planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citation visibility as part of SEO. Use when user says "content brief", "blog brief", "write brief", "SEO brief", "article brief", or "content requirements".

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。

Audit and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes advisory editorial style diagnostics (sentence-length variation, configured phrase lists, vocabulary sampling) that never infer authorship or affect scoring. Supports export formats (markdown, JSON, table) and batch analysis with sorting. Generates prioritized recommendations (Critical/High/Medium/Low) with specific fixes. Works with any format (MDX, markdown, HTML, URL). Use when user says "analyze blog", "audit blog", "blog score", "check blog quality", "blog review", "rate this blog", "blog health 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。

Generates guidance for reliability, resilience, availability, redundancy, fault-tolerance, and disaster recovery (DR) for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use when the user asks to evaluate, design, or improve the reliability, resilience, availability, or disaster recovery capabilities of Google Cloud workloads.

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。

Provides guidance for troubleshooting Apache Airflow DAGs (failed DAG runs and task instances) in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Use when figuring out reasons for DAG run or task instance failures. Don't use when looking for overall recommendations for Managed Airflow environment performance.

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。

Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.

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。

Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

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 deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.

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。

Scan code for security vulnerabilities, misconfigurations, and exposed secrets. Use when a user asks to audit security, find vulnerabilities, check for OWASP issues, scan for secrets, review dependencies for CVEs, detect SQL injection, find XSS vulnerabilities, or harden an application. Covers OWASP Top 10, dependency auditing, secrets detection, and generates fix recommendations with severity ratings.

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。

Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations.

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。

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.

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。

Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.

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。

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.

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。

Checks structured logging, health check endpoints, metrics collection, request tracing, log levels. Returns findings with severity, location, effort, recommendations.

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。

Checks compiler/linter errors, deprecation warnings, type errors, failed tests, build config issues. Returns findings with severity, location, effort, recommendations.

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。

Checks hardcoded secrets, SQL injection, XSS, insecure dependencies, missing input validation. Returns findings with severity, location, effort, recommendations.

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。

Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

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 multi-criteria decision analysis for ranking options with weights, constraints, confidence, tradeoff reasoning, sensitivity analysis, and explainable recommendations. Use when the user asks for decision support, MCDA, weighted scoring, prioritization, vendor selection, route planning, hiring shortlist ranking, tool comparison, procurement decisions, or auditable agent decision logic.

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。

Save any product to a universal wishlist. Converts any product URL into a one-click "save for later" link. Works with any retailer, any AI platform, zero setup.

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。

Adaptive testing engine with IRT/CAT, AI question generation, and personalized learning recommendations

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。

Produces U.S. litigation case chronologies with dated timelines, executive summaries, source attribution, gap analysis, and investigation recommendations. Use when asked for a chronology, timeline, case summary, or executive summary of a legal matter, or during case intake, deposition prep, or trial 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。

Produces a Rule 506(d) bad actor disqualification review for private securities offerings, including a covered persons register, tailored questionnaires mapping to each disqualifying event category, a documented reasonable-care diligence record, and classification analysis of flagged events with remediation or disclosure recommendations. Use this skill when conducting Rule 506(d) diligence, identifying covered persons for a Regulation D offering, drafting bad actor questionnaires, or analyzing potential disqualifying events involving criminal convictions, SEC orders, SRO sanctions, or state regulatory actions. Also trigger when the user mentions bad actor screening, covered persons analysis, Rule 506(d) questionnaire, disqualification waiver, or reasonable care defense. Even if the user just says "bad actor check" or "506(d) diligence," use this skill.

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 for Vue 3 testing best-practices review and recommendations — designing and auditing Vitest + Vue Test Utils tests for components, composables, Pinia stores, Vue Router, async/Suspense, Teleport, forms, and accessibility, plus Playwright E2E test-design strategy. Advisory/review only — recommends patterns and flags test smells; does not run tests. Complements mk:vue-best-practices (feature code). Invoke for "review my Vue tests", "how should I test this component/composable/store", or "Vue test best practices".

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 writing, reviewing, or refactoring Vue 3 code — components, composables, reactivity, Pinia state, Pinia Colada data-fetching, file-based routing, and forms. Targets Composition API + <script setup> + TypeScript. Auto-activates on .vue files. For deep best-practices review/recommendations or the full ordered workflow (built-in components, animations, performance pass), use mk:vue-best-practices.

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。

Read-only audit of `.claude/` structural overhead. Reports prioritized "remove X save Y tokens" recommendations against the model context window. NOT for monetary cost tracking — that's /mk:budget. NOT for transcript size monitoring — long-session continuity defers to Claude Code native compaction. NOT for runtime context decisions (what to read, when to compact) — see mk:context-engineering. Use when planning to add context capacity, diagnosing perceived slowdowns, or auditing health.

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。