2,413 件 ・ 関連度順
概要と使いどころ
Assess a public HTTP(S) page before building browser automation, extraction, or an integration. Use this skill to collect bounded structural evidence, readiness signals, risk flags, acceptance tests, and remediation priorities without sending credentials or accessing private 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。
Manages ArgoCD application synchronization using the ArgoCD REST API and argocd CLI. Handles sync waves, hooks, and health assessments for GitOps-driven Kubernetes deployments.
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Automates ArgoCD application synchronization using the ArgoCD gRPC/REST API and argocd-autopilot CLI. Manages ApplicationSets, sync waves, and health assessments for Kubernetes deployments.
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。
Expert product strategist for vision, strategy, and market positioning. Use when defining product vision, assessing product-market fit, sizing market opportunities (TAM/SAM/SOM), competitive positioning, or choosing between build/buy/partner. Covers business model design, monetization strategy, platform decisions, and strategic roadmap planning.
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。
Expert Architecture Decision Record (ADR) creation and lifecycle management based on Olaf Zimmermann's methodology. Use when creating ADRs, reviewing architectural decisions, evaluating decision readiness, writing MADR templates, assessing decision quality, or managing ADR logs. Covers the full lifecycle from readiness (START criteria) through creation, MADR formatting, completion (ECADR criteria), and ongoing maintenance.
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。
The Mileva Method (CRISP) — Phase 4: Spec. Full implementation readiness package including solution design, UX direction, tech stack, backlog, MVP prioritization, risk assessment, and AI architecture for Claude Code projects — CLAUDE.md, skill mapping, AI specs, sprint planning, quality gates. Triggers on "spec", "phase 4", "build ready", "implementation plan", "CLAUDE.md", "sprint planning", "backlog", "AI spec", or after Phase I exit checklist is complete.
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Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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。
Architecture design skill: ADR records, system design checklists, scalability assessment, architecture patterns. Use for complex system design and architecture decisions.
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 SEO analysis for any website or business type. Performs full site audits, single-page deep analysis, technical SEO checks (crawlability, indexability, Core Web Vitals with INP), schema markup detection/validation/generation, content quality assessment (E-E-A-T framework per Dec 2025 update extending to all competitive queries), image optimization, sitemap analysis, and Generative Engine Optimization (GEO) for AI Overviews, ChatGPT, and Perplexity citations. Analyzes AI crawler accessibility (GPTBot, ClaudeBot, PerplexityBot), llms.txt compliance, brand mention signals, and passage-level citability. Industry detection for SaaS, e-commerce, local business, publishers, agencies. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "page speed", "structured 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。
Assess team structure against Skelton's Team Topologies. Evaluate cognitive load, interaction modes, and Conway's Law alignment.
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 to assess regulatory applicability for products that may fall under AI regulation (EU AI Act, Article 50 transparency).
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 to assess Privacy by Design compliance and GDPR/data protection alignment for a feature or 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。
Design the smallest viable test to validate or invalidate a critical assumption. Based on Torres's assumption testing framework, organized by Gilad's AFTER model (Assessment → Fact-Finding → Tests → Experiments → Release 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。
Use to evaluate the current state of a diamond. Checks theory gates, confidence levels, and recommends next action.
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 delivery health metrics. For software: DORA + APEX. For content/AI/service products: product-type-appropriate metrics.
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 special dividend catalysts with balance sheet capacity, tax efficiency, and shareholder return comparison analysis. Use when modeling special dividends, evaluating capital return catalysts, or assessing dividend capacity.
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Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.
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Builds renewable energy yield models with resource assessment, capacity factor analysis, and P50/P90 production estimates. Use when modeling wind/solar yields, analyzing resource data, or evaluating production uncertainty.
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 structural interest rate exposure with fixed/floating mismatch, basis risk, and cap/floor adequacy assessment. Use when modeling structural rate risk, analyzing basis risk, or evaluating interest rate hedging needs.
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Calculates potential future exposure and CVA with simulation-based approaches and netting agreement analysis. Use when modeling counterparty exposure, calculating CVA/DVA, or assessing counterparty risk.
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Builds PIK and PIK toggle models with compound interest analysis, cash vs PIK election scenarios, and leverage impact assessment. Use when modeling PIK instruments, analyzing toggle mechanics, or evaluating accrued interest impact.
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。
Compares build vs buy alternatives with risk-adjusted returns, time-to-value, and execution probability assessment. Use when evaluating growth strategies, comparing M&A vs organic investment, or analyzing make-vs-buy decisions.
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 pricing models incorporating J-curve positioning with blind pool risk, early-vintage assessment, and age-weighted adjustments. Use when pricing early-vintage funds, analyzing J-curve risk, or adjusting for fund maturity.
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。
Evaluates LP portfolio rebalancing pressure from denominator effects with over-allocation analysis and pace adjustment recommendations. Use when analyzing denominator effects, assessing LP allocation constraints, or modeling portfolio rebalancing.
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。