4,514 件 ・ 関連度順
概要と使いどころ
Statute and regulation interpretation framework. Use when reading statutes, classifying requirements, analyzing operative keywords, applying canons of construction, or mapping compliance obligations from legislative text.
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 tokens, light/dark theming, and WCAG contrast validation for HTML documents and decks, compiled into one inlinable CSS bundle. Use when theming a report or deck, auditing contrast, or fixing dark-mode color drift.
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。
Assess IT vendors and third-party partners with multi-factor risk scoring and regulatory compliance checklists. Use when evaluating technology vendors.
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 templated responses for common legal inquiries with escalation detection. Use when drafting legal responses.
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。
Convert markdown into a self-contained HTML slide deck with layouts, speaker notes, keyboard navigation, and a content-density linter. Use when building a deck from markdown, cutting an overloaded deck, or timing a talk.
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。
Data breach incident response with ENISA severity scoring, notification timelines, and compliance tracking. Use for breach assessment and response.
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 and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
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 legal risk assessment with 5x5 Severity x Likelihood matrix. Use for risk scoring, risk registers, escalation decisions, and risk memos.
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。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
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。
App Store Optimization toolkit for researching keywords, optimizing metadata, and tracking mobile app performance on Apple App Store and Google Play Store.
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。
This skill should be used when the user asks to "plan a red team engagement", "scope a penetration test", "design a security assessment methodology", "create rules of engagement", or "plan an adversary simulation".
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 calibrated interview loops, competency-based question banks, and hiring calibration. Use when designing interview processes, creating hiring pipelines, generating scoring rubrics, analyzing interviewer bias, or building question banks.
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 SaaS boilerplate with auth, database schemas, Stripe billing, multi-tenancy, API routes, and dashboard UI on a Next.js/TypeScript/Tailwind stack. Use when starting a new SaaS product, subscription app, or multi-tenant platform.
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。
Security audit and vulnerability scanning for AI agent skills before install. Detects prompt injection, dangerous code, exfiltration, credential harvesting, and supply chain risks. Use when evaluating untrusted skills or gating installs.
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。
This skill should be used when the user asks to "audit prompts for safety", "check prompts for injection vulnerabilities", "manage a prompt catalog", "version control prompts", or "review prompt quality and compliance".
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。
Automates release management with changelog generation, semantic versioning, and release readiness checks. Use when preparing releases, generating changelogs, bumping versions, or validating release candidates.
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。
Performance profiling for Node.js, Python, and Go: CPU flamegraphs, memory leak detection, bundle analysis, query optimization, and k6 load testing. Use when diagnosing slow endpoints, memory growth, large bundles, or traffic spikes.
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。
Production incident response. Use when handling incidents, classifying severity, reconstructing timelines, writing postmortems, generating comms templates, or building response playbooks with severity scoring and RCA frameworks.
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 asks to "design cloud architecture", "set up Terraform infrastructure", "optimize cloud costs", "plan disaster recovery", "configure multi-region failover", "audit IAM policies", "migrate to cloud", "set up VPC networking", "compare AWS vs GCP vs Azure", or "right-size cloud instances". Expert cloud architecture covering AWS, GCP, Azure, multi-cloud strategy, cost optimization, security, and infrastructure automation.
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。
Patterns for AI agents that learn from their own execution, detect failure modes, and improve autonomously. Use when building agents that get better over time, managing auto- memory, or designing self-correcting feedback loops.
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。
Multi-agent source security audit with a coverage ledger, independently verified findings, and machine-checked records. Use when asked to audit a codebase, find vulnerabilities, or run a source-level pen test.
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。
ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization.
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。
STRIDE threat modeling, DREAD risk scoring, secret detection, and secure architecture design. Use when conducting threat models, reviewing code for vulnerabilities, designing defense-in-depth, or scanning for hardcoded secrets.
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 operational runbooks from codebase analysis covering deployment, incident response, scaling, and monitoring, with copy-paste commands and rollback steps. Use when bootstrapping ops docs, preparing for on-call, or post-incident.
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。