6,861 件 ・ 関連度順
概要と使いどころ
Organizational Development Manager (R31): guides the subject from an organizational change request (self/team/organization) to a concrete first step from SE/SM/PE. Step 0 — system type classifier (MIM.M.030, 7 questions). Step 3 — routing-table (MIM.M.031).
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。
Intelligent financial management skill for Claude Code that provides comprehensive PocketSmith API integration with AI-powered analysis, transaction categorization, rule management, tax intelligence, and scenario planning. Use when working with PocketSmith data for (1) Transaction categorization and rule management, (2) Financial analysis and reporting, (3) Australian tax compliance (ATO) and deduction tracking, (4) Scenario analysis and forecasting, (5) PocketSmith setup health checks, (6) Budget optimization and spending insights.
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。
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for parser differentials, HTTP normalization gaps, ambiguous headers, path decoding drift, transfer-framing mismatches, and request smuggling routes. Use when the user asks to trace proxy and backend parse differences, conflicting path normalization, Host or forwarded-header ambiguity, CL/TE issues, or routing outcomes that differ across hops. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Advanced Docker containerization expert for multi-stage builds, image optimization, security hardening, and Compose orchestration. Use when the task involves `working with Dockerfile`, `docker-compose.yml`, `containerization`, `multi-stage builds`, or `optimizing Docker images`.
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。
Structures post-offering stabilization with overallotment option exercise, market support, and penalty bid mechanisms. Use when managing stabilization, exercising greenshoe options, or analyzing aftermarket support.
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 content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
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 websites for AI search visibility (GEO/SEO) and generates deployable artifacts (llms.txt, schema JSON-LD, robots.txt). 7-dimension scorecard tailored by site type and size, grounded in Princeton KDD 2024, Toronto 2025, and ICLR 2026 research. This skill should be used when optimizing for ChatGPT, Perplexity, Google AI Overviews, or other AI search engines. Also triggered by queries about AI search optimization, generative engine optimization, llms.txt, AI crawler configuration, schema markup for AI, citation optimization, or Google AI Mode.
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。
Apply React and Next.js performance optimization guidelines from Vercel Engineering — 40+ rules covering components, data fetching, bundle optimization, and rendering. Triggers on React components, Next.js pages, bundle optimization, performance improvements, refactoring React code.
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。
Preserve and conserve library and archival materials. Covers environmental controls (temperature, humidity, light), handling procedures, book repair techniques (torn pages, loose spines, foxing), acid-free storage, digitization for preservation, and disaster recovery planning. Use when establishing preservation practices for a new or existing collection, when materials show signs of deterioration, when setting up environmental controls for storage, when planning digitization to preserve fragile originals, or when creating a disaster recovery plan for a library or archive.
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。
Implement cloud cost optimization strategies for Kubernetes workloads using tools like Kubecost for visibility, right-sizing recommendations, horizontal and vertical pod autoscaling, spot/preemptible instances, and resource quotas. Covers cost allocation, showback reporting, and continuous optimization practices. Use when cloud costs are growing without proportional business value, when resource requests are misaligned with actual usage, when manual scaling leads to over-provisioning, or when implementing showback and chargeback for internal cost accountability.
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。
Guide a person through healing modalities including energy work (reiki, chakra balancing), herbal remedies, basic first aid stabilization, and holistic techniques (breathwork, visualization, body scan). AI coaches the practitioner through assessment triage, modality selection, energetic connection, remedy preparation, and integration. Use when a person describes a physical ailment or injury, reports energetic imbalance (fatigue, emotional stagnation), wants coaching through a holistic breathwork or visualization session, or needs post-meditation integration with directed healing attention.
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。
Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.
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。
Create interactive maps, elevation profiles, and spatial visualizations from GPX tracks, waypoints, or route data using R (sf, leaflet, tmap) or Observable (D3, deck.gl). Covers data import, coordinate system handling, map styling, and export to HTML or image formats. Use when visualizing a planned or completed tour route on an interactive map, creating elevation profiles for hiking or cycling routes, overlaying waypoints and POIs on a basemap, or building a web-based trip dashboard.
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。
Create R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the neon-glow output. Use when a new entity has been added and needs a visual icon for the force-graph visualization, an existing glyph needs replacement, or when batch-creating glyphs for a new domain.
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。
Address unwanted dog behaviors through desensitization, counter-conditioning, and management. Covers reactivity (to dogs, people, sounds), separation anxiety, resource guarding, excessive barking, and leash pulling using force-free methods with systematic threshold management. Use when a dog shows reactivity toward other dogs, people, or stimuli; when separation anxiety causes destructive behavior or vocalization; when resource guarding is present; or when behaviors like excessive barking or leash pulling interfere with daily life — after basic obedience is established.
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 prime numbers using primality tests, factorization algorithms, prime distribution analysis, and sieve methods. Covers trial division, Miller-Rabin, Sieve of Eratosthenes, and the Prime Number Theorem. Use when determining whether an integer is prime or composite, finding prime factorizations, counting or listing primes up to a bound, or investigating prime properties within a number-theoretic proof or computation.
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。
End-to-end automated model quantization and accuracy tuning workflow. Use when user asks for automated model quantization and accuracy tuning, e.g. "自动量化", "量化调优", "一键量化", "精度调优", etc. 当用户给出多卡（≥2 卡）卡号时，量化阶段通过 EP 并行适配（msmodelslim-ep-parallel-adaptation）保证多卡 EP 并行，调优主流程仍在本 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。
Design AI personalization engines for content. TRIGGERS - Use when user needs help with ai-personalization-engine related tasks.
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。
Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL support.
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。
"Apply Weick's sensemaking theory to analyze how individuals and organizations construct meaning from ambiguous situations. Use this skill when the user needs to analyze organizational responses to crises, understand how interpretive frames shape action, diagnose breakdowns in collective understanding, or when they ask 'how did they interpret this situation', 'why did the organization fail to see the warning signs', or 'how do people make sense of disruption'.".
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。
"Apply organizational ecology (Hannan and Freeman) to analyze population-level dynamics of organizational founding, failure, and selection. Use this skill when the user needs to explain industry-level patterns of birth and death rates, analyze structural inertia and liabilities of newness or aging, evaluate why adaptation is rare relative to selection, or when they ask 'why do most startups fail', 'why is this industry dominated by old firms', or 'why do organizations resist change despite environmental pressure'.".
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。
Chọn đúng biểu đồ, kể chuyện với số liệu, và tránh误导 — dựa trên nguyên tắc từ Kieran Healy (Data Visualization, Princeton 2019) và taxonomy từ AntV chart-visualization-skills. Dùng khi cần quyết định loại chart, trình bày insight cho stakeholder, hoặc kiểm tra xem figure có gây hiểu lầm không. Để vẽ Python thực tế, chuyển sang matplotlib / seaborn / scientific-visualization.
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。
"Net-zero transition playbook: GHG inventory (ISO 14064-1, GHG Protocol Scope 1/2/3), science-based targets (SBTi), TCFD and ISSB S1/S2 climate disclosure, Taiwan carbon fee, decarbonization roadmap, internal carbon pricing, supply-chain carbon, product carbon footprint, green electricity and T-REC. Use for corporate decarbonization roadmap, carbon inventory, carbon-fee response, TCFD/ISSB reporting, supply-chain decarbonization, or responding to international customers (Apple, RE100). Triggers: 『碳盤查』『SBTi』『碳費』『TCFD』『淨零路徑』『範疇 3』『綠電』『CBAM』『ISO 14064』『ISSB』『T-REC』. For Taiwan EMBA ESG/sustainability/operations/strategy/finance cases. Focuses on Taiwan listed-company and supply-chain practice; sustainability strategy theory: use Asgard `grad-sustainability`; ERM 框架整合氣候風險: use `biz-erm`; 董事會 ESG 委員會結構設計: use `biz-corporate-governance`; 併購 ESG 盡職調查: use `fin-m-and-a`.".
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。