7,148 件 ・ 関連度順
概要と使いどころ
Use when asked to select chart types for analytics dashboards, choose BI visualizations, or design data displays. Examples: "best chart for sales data", "dashboard visualization for metrics", "analytics chart selection"
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 cloud infrastructure costs and produce a concrete optimization plan with specific changes and estimated savings. Use when asked to "how much is this costing", "reduce cloud spend", "cost optimization", "are we overpaying", "cloud bill", or "budget for this infra".
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。
Measurement techniques for identifying composition, microstructure, and properties of engineering materials — optical and electron microscopy, x-ray diffraction, EDS and WDS spectroscopy, thermal analysis, mechanical testing, and fractography. Covers when to use which technique, sample-preparation pitfalls, and how to build a characterization plan that answers a specific engineering question rather than accumulating data for its own sake.
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。
Calculus, series, numerical methods, and optimization for computational mathematics. Covers limits (epsilon-delta, L'Hopital, squeeze theorem), derivatives (rules, optimization, related rates), integrals (Riemann sums, Fundamental Theorem of Calculus, integration techniques), series (convergence tests, Taylor and Maclaurin expansions), differential equations (separable, linear, exact), numerical methods (Newton-Raphson, Euler method, Simpson's rule), and computational pitfalls (floating-point arithmetic, catastrophic cancellation, numerical stability). Use when computing derivatives, integrals, limits, series, solving differential equations, or analyzing numerical accuracy.
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。
A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from 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。
Atomic theory, periodic table organization, electron configuration, periodic trends, and isotopes/radioactivity. Covers Dalton through quantum mechanical models, electron shell filling (Aufbau, Hund, Pauli), periodic law and block structure, trend prediction (electronegativity, ionization energy, atomic radius, electron affinity), isotope notation, nuclear stability, and radioactive decay modes. Use when teaching, problem-solving, or reasoning about atomic-level chemistry.
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。
OpenStack capacity planning operations skill for resource planning, quota management, and scaling decisions. Covers compute capacity (allocation ratios, vCPU/RAM utilization, host aggregates, availability zones), storage capacity (Cinder pool sizing, thin provisioning, Glance storage, Swift rings), network capacity (floating IP pools, port quotas, subnet sizing), project quota management (templates for small/medium/large profiles), flavor sizing strategy, utilization analysis with placement service, growth forecasting from historical metrics, and right-sizing recommendations for underutilized resources.
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。
OpenStack Keystone identity service skill for deploying, configuring, operating, and troubleshooting the authentication and authorization backbone of an OpenStack cloud. Covers identity management, token lifecycle (Fernet provider with rotation), service catalog registration, RBAC policy customization, domain/project/user hierarchy, federation basics (SAML/OIDC), credential encryption, and endpoint management. Use when deploying Keystone via Kolla-Ansible, managing users and projects, debugging 401 errors, rotating Fernet keys, configuring RBAC policies, or integrating services through the service catalog.
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。
Generalization and composition of constraints across navigators
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。
Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).
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 AgentDB with quantization, HNSW tuning, caching, batch ops, and pruning.
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 AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
账号定位阶段做战略选择时用：用不可能三角（内容深度/传播力/变现力不可兼得）决定放弃哪个角，选IP路线（深度+变现，抗周期/高商业化/复利）或泛流量路线（传播力，但转化差不值钱）。Trigger："追粉丝还是做IP""IP还是泛流量""定位怎么选""深度和传播怎么权衡""泛流量不值钱吗""IP vs generic traffic""build IP or chase followers"。不适用：已有定位后的内容生产/选题（→内容创作类skill）；已有粉丝问怎么变现（→x-monetization-pyramid）；找对标账号（→x-benchmark-research）。
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。
规划变现路径/判断够不够格开创作者收益/决定卖什么产品时使用。三层金字塔定位：底层流量型(商单+广告分成,需500蓝V+3月5M曝光)、中层产品型(课程/付费专栏/带货)、顶层服务型(咨询/高端社群,利润率>80%)。IP路线可叠三层,泛流量卡底层。Trigger："怎么变现""够不够格开收益""卖什么产品""monetize""creator revenue""what to sell"。不适用：没粉丝的冷启动(→x-cold-start-playbook)、选IP还是泛流量(→x-positioning-tradeoff)、开蓝V/装修(→x-account-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。
Optimize for search engine visibility and ranking. Use when the task involves `improve SEO`, `optimize for search`, `fix meta tags`, `add structured data`, `sitemap optimization`, or `search engine 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。
Optimize existing CLAUDE.md, SKILL.md, agent definitions, and other AI-facing files for Claude comprehension and economy. Scope: optimization of existing content only — not upstream sync, not read-only auditing. Measures baseline metrics, delegates to the ai-doc-optimizer agent with file-type-specific context, runs independent verification via second agent, measures post-optimization metrics, and presents comprehensive before/after report. Supports iterative mode for large targets. Use when improving prompt effectiveness, reducing token waste, or rewriting instructions for LLM consumption. Invoke with /optimize-claude-md <file-or-directory>.
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。
Review a change for security defects such as secret exposure, injection, authentication/authorization failures, unsafe deserialization, and dependency risk. Use for an independent security perspective on a defined change set.
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 PLAN artifact from SAM Stage 2 needs contextualization against actual codebase state — grounds the design plan in reality by performing scope analysis (NEW/MODIFY/COMPLETE classification), conflict detection between plan assumptions and codebase patterns, and resource mapping to concrete file paths and integration points. Produces an updated ARTIFACT:PLAN registered via MCP with a Contextualization section appended.
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。
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging strategy.
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。
When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions "exit intent," "popup conversions," "modal optimization," "lead capture popup," "email popup," "announcement banner," or "overlay." For forms outside of popups, see form-cro. For general page conversion optimization, see page-cro.
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 spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
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 spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
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。
Choose the right serialization format for .NET applications. Prefer schema-based formats (Protobuf, MessagePack) over reflection-based (Newtonsoft.Json). Use System.Text.Json with AOT source generators for JSON scenarios.
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 for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine 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。