2,113 件 ・ 関連度順
概要と使いどころ
Use for due diligence, legal-financial risk review, investment or business transaction checklists, and preliminary screening where facts, documents, assumptions, legal uncertainty, debt/equity, assets/liabilities, contracts, tax, regulatory, compliance, technology/product, and financial-model issues must be separated clearly.
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 HIPAA compliance assistant for healthcare and software contexts. Use this skill whenever the user mentions HIPAA, PHI (Protected Health Information), ePHI, covered entities, business associates, healthcare data privacy, medical records, health information security, BAA (Business Associate Agreements), or any compliance review involving patient data. Also trigger for requests to draft privacy notices, HIPAA policies, consent forms, security risk assessments, or breach notification letters. Use for developers building healthcare software who need technical safeguard guidance (encryption, access controls, audit logs), compliance officers reviewing documents or procedures, and anyone asking "is this HIPAA compliant?" or "what does HIPAA require for X?". When in doubt about whether a healthcare or data privacy question falls under this skill — use it.
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。
Turn complex legal analysis into clear, commercially useful client-facing advice. Use this whenever the user has dense legal material — drafting, internal analysis, counsel notes, research memos, pleadings, a case update, or correspondence — and wants it converted into something a client can actually understand and act on. Trigger on phrases like 'explain this to the client', 'put this in plain English', 'translate this for a non-lawyer', 'turn this into client-facing advice', 'make this client-ready', 'draft a client update', or when the user shares legal analysis and asks 'what does this mean for them'. Also trigger when the user wants a board summary, litigation risk update, or call script derived from legal material. The skill preserves legal nuance, uncertainty, and risk rather than oversimplifying — it makes advice usable, not just simpler.
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。
Works out which documents you have to hand over to the other side in a civil case in England & Wales, and builds the formal list. The part it gets right that trips people up is which disclosure regime applies — Practice Direction 57AD (the Disclosure Pilot, now permanent in the Business and Property Courts, with its Models A–E) or standard disclosure under CPR Part 31 everywhere else. It picks the regime, chooses a Model per issue, structures the Disclosure Review Document, and drafts the disclosure certificate for the party to sign personally. Built for litigation juniors, in-house counsel, and small teams without a precedent bank. Use when the user says 'disclosure list', 'PD 57AD', 'Model C', 'extended disclosure', 'List of Documents', 'N265', or needs to work out what must be disclosed.
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 CMMC 2.0 (Cybersecurity Maturity Model Certification) advisor for US defense contractors and subcontractors in the Defense Industrial Base (DIB). Use this skill whenever a user asks about CMMC 2.0, CMMC Level 1, Level 2, or Level 3, DoD cybersecurity compliance, NIST SP 800-171, CUI (Controlled Unclassified Information) protection, System Security Plan (SSP), Plan of Action & Milestones (POA&M), C3PAO assessments, DIBCAC audits, self-assessment, SPRS score, or any requirement under DFARS 252.204-7012 or 7021. Also trigger for: "CMMC gap analysis", "CMMC readiness", "FCI protection", "CUI scoping", "CMMC practices", "DoD contract cybersecurity", "defense supply chain security", or "prime contractor flow-down 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。
Audits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to the evidence, reasoning basis, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.
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。
Verify a game with evidence on its selected target runtime. Launch the actual build and prove real rendering, input, the core loop, at least one designed outcome, restart, and explicit limitations without dressing subjective fun up as a certain verdict. Use for test a generated game, QA a game build, check whether the game is fully playable, or verify the build. 游戏证据化质量验证。在选定的目标运行环境中启动实际构建，证明真实渲染、输入、核心循环、至少一个设计结果、重开和明确限制，不把主观趣味包装成确定性结论。用于测试生成游戏、检查游戏能否完整游玩或验证构建。
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 blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.
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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.
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 blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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 blueprint for racing games including vehicle physics (VehicleBody3D, suspension, friction), checkpoint systems (prevent shortcuts), rubber-banding AI (keep races competitive), drifting mechanics (reduce friction, boost on exit), camera feel (FOV increase with speed, motion blur), and UI (speedometer, lap timer, minimap). Use for arcade racers, kart racing, or realistic sims. Trigger keywords: racing_game, vehicle_physics, checkpoint_system, rubber_banding, drifting_mechanics, camera_feel.
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 blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.
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 blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.
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 blueprint for racing games including vehicle physics (VehicleBody3D, suspension, friction), checkpoint systems (prevent shortcuts), rubber-banding AI (keep races competitive), drifting mechanics (reduce friction, boost on exit), camera feel (FOV increase with speed, motion blur), and UI (speedometer, lap timer, minimap). Use for arcade racers, kart racing, or realistic sims. Trigger keywords: racing_game, vehicle_physics, checkpoint_system, rubber_banding, drifting_mechanics, camera_feel.
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。
Add a custom domain to a Temps project and provision an automatic SSL/TLS certificate via Let's Encrypt, driven entirely from the `@temps-sdk/cli` CLI. Handles subdomains, apex domains, HTTP-01 and DNS-01 challenges, and wildcard domains. Use when the user wants to: (1) Add a custom domain to their Temps app, (2) Set up HTTPS/SSL for a deployment, (3) Point their own domain at a Temps project, (4) Add a wildcard domain, (5) Configure DNS for Temps. Triggers: "add custom domain", "point my domain at temps", "set up ssl", "https for my app", "wildcard domain", "add domain to project".
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。
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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 offer code distribution strategies and configuration guides for subscription and IAP promotions — including partner campaigns, influencer programs, and email re-engagement. Use when setting up offer codes for distribution.
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。
Classes and statistical methods for large SNP association studies. This extends the earlier snpMatrix package, allowing for uncertainty in genotypes.
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。
Gene Expression Omnibus(GEO) and The Cancer Genome Atlas (TCGA) provide us with a wealth of data, such as RNA-seq, DNA Methylation, SNP and Copy number variation data. It's easy to download data from TCGA using the gdc tool, but processing these data into a format suitable for bioinformatics analysis requires more work. This R package was developed to handle these 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。
Generate SuperSigs (supervised mutational signatures) from single nucleotide variants in the cancer genome. Functions included in the package allow the user to learn supervised mutational signatures from their data and apply them to new data. The methodology is based on the one described in Afsari (2021, ELife).
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 package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
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 knowledge for Azure Networking development including troubleshooting, best practices, decision making, architecture & design patterns, security, and configuration. Use when designing VNets/VWAN, load balancers, firewalls/WAF, DDoS protection, or Virtual Network Manager policies, and other Azure Networking related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Virtual WAN (use azure-virtual-wan), Azure Network Watcher (use azure-network-watcher).
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 knowledge for Azure IoT development including decision making, architecture & design patterns, and configuration. Use when managing Azure Device Registry X.509 PKI, ADR policies, IoT Hub cert revocation, or device schema namespaces, and other Azure IoT related development tasks. Not for Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Defender For Iot (use azure-defender-for-iot).
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。