806 件 ・ 関連度順
概要と使いどころ
Use when a task needs the judgment of a museum or gallery curator — evaluating whether to accept a donated collection or object, writing an acquisition or deaccession recommendation, resolving a provenance or repatriation question, deciding a loan request, or drafting exhibition label copy.
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 a task needs the judgment of a Concierge — securing a reservation at a fully-booked restaurant or sold-out venue, coordinating a multi-vendor guest request (dinner, transportation, and a gift delivery) inside a tight window, deciding when to pivot from a failed Plan A to a same-caliber Plan B, or navigating a paid-referral relationship without letting the commission distort the recommendation.
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 a project to detect configured quality and testing tools across JVM (Gradle/Maven), Android (AGP/Compose/KMP), Node.js/TypeScript, and Python ecosystems. Cross-reference against research-backed recommendations and assist with setup. Auto-detects project type(s) including monorepos with mixed ecosystems. Use when user asks to "audit tooling", "recommend tools", "quality stack", "what tools am I missing", "setup eslint", "setup detekt", "add coverage", "add ruff", "configure CI quality pipeline", "scan project tools", "tooling audit", "android tooling", "android quality", "compose testing", "kmp testing", or "screenshot testing".
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 wants to deploy a local directory or GitHub repository to Volcengine and needs the project analyzed, the app shape understood, and a ranked recommendation across ECS, VKE, and veFaaS before choosing an execution path. Also trigger when the user asks "what deploy mode should I use", "is this repo ready for Volcengine", or "check my repo before deploying". This skill prepares the decision; `volcengine-deploy` skill performs the chosen deployment, and `volcengine-iac` skill is used only when the user chooses Terraform/IaC or the task already has an IaC workflow.
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 a 2026-grade content brief for a target query — combines classic SERP analysis with AI Overview / Perplexity / ChatGPT citation analysis, entity recommendations (target ≥15 recognized entities), topical authority gap map, intent-mapped heading structure, internal linking targets.
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。
Analyzes infrastructure costs at 1K-100K user scales by reading the actual codebase, auto-detecting cloud providers, modeling per-action costs, and projecting total monthly spend with optimization 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。
Write a compelling sales proposal. Use when the user says "write a sales proposal", "put together a proposal", "draft a proposal for this prospect", "create a business case", "write up our recommendation", "how to structure a proposal", "proposal template", "executive summary for a deal", or wants to create a written document that moves a prospect toward a decision.
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。
Write an executive summary using the Pyramid Principle SCQA structure. Use when a consultant says "write an executive summary", "I need a one-pager for the exec", "how do I open this report", "write me the intro for this deck", "draft the cover memo", "I need to frame the findings", "executive doesn't have time to read the full report", "help me write the storyline", or "write the situation-complication-answer". Also trigger when someone has findings or recommendations and needs to communicate them top-down to a time-constrained audience.
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。
Post-writing SEO validation with pass/fail checklist covering title tag length and keyword placement, meta description quality, heading hierarchy and keyword density, internal/external link audit with anchor text analysis, canonical URL verification, Open Graph meta tags (og:title, og:description, og:image), Twitter Card validation, structured data presence and validity, URL structure optimization, and image alt text presence. Produces prioritized fix list with specific recommendations. Use when user says "seo check", "check seo", "validate seo", "blog seo", "seo validation", "on-page seo", "title tag check", "meta description check", "heading check", "link 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。
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。
Detect keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports local-only mode (grep-based) and DataForSEO API mode (Page Intersection endpoint at ~$0.01/call). Outputs severity-scored report with merge or differentiate recommendations. Use when user says "cannibalization", "keyword overlap", "competing pages", "duplicate keywords", "cannibalize".
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 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。
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks 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。
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。
Guides users through discovering their database requirements, recommends a Google Cloud database based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?', 'Help me pick a database', or when a user wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or database migrations.
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。
AI Concierge โรงแรม — guest journey, recommendation matrix, request handling, complaint resolution, รองรับ guest ไทย+ต่างชาติ
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-compaction housekeeping. Walks a checklist (persistent memory updates, git hygiene, trash cleanup) plus an open-judgment audit, produces an SBAR with a go/no-go recommendation, and emits a copy-pasteable resume prompt for the post-compaction agent if work remains. Run this immediately before /compact.
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。