6,706 件 ・ 関連度順
概要と使いどころ
Debug Kubernetes pods, nodes, and workloads. Use when pods are failing, containers crash, nodes are unhealthy, or users mention debugging, troubleshooting, or diagnosing Kubernetes issues.
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 PCI DSS compliance advisor covering PCI DSS v4.0.1 (current) and v4.0. Use this skill whenever a user asks about PCI DSS, payment card security, cardholder data protection, CDE scoping, SAQ types (A, A-EP, B, B-IP, C, C-VT, P2PE, D), ROC, AOC, QSA assessments, ASV scans, merchant levels, service provider levels, network segmentation, penetration testing, tokenisation, encryption of PAN data, or any of the 12 PCI DSS requirements. Also trigger for questions like "are we PCI compliant?", "how do I scope my CDE?", "which SAQ applies to us?", "what changed in PCI DSS v4.0?", "how do I prepare for a QSA audit?", or any request involving payment data security, cardholder data environment, or PCI certification readiness.
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, review, and validate Google Cloud (GCP) architectures. Use when choosing GCP compute, storage, networking, or identity services, or applying the Google Cloud Architecture Framework (reliability, security, cost, performance).
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。
DevOps for CI/CD, containers, Kubernetes, and Terraform. Use when building pipelines, containerizing apps, managing clusters, provisioning cloud infra, deploying with blue- green/canary, or handling infrastructure incidents.
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。
This skill should be used when the user asks to "analyze Helm charts", "validate Helm values", "review chart structure", "check Kubernetes Helm templates", or "audit chart dependencies and configuration".
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, review, and validate Azure cloud architectures. Use when choosing Azure compute, storage, networking, or identity services, or applying the Azure Well-Architected Framework to a workload.
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。
In-app paywall and upgrade screen optimization covering feature gate design, usage limit UX, trial expiration flows, upgrade trigger timing, save offer strategy, and ethical monetization patterns.
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。
Phylogenetic tree construction, analysis, and evolutionary inference
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 .NET 8 applications with minimal APIs, clean architecture, cloud-native microservices, Entity Framework Core, CQRS with MediatR, and AOT compilation.
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 C# applications with .NET 8+, ASP.NET Core APIs, Blazor web apps, Entity Framework Core, async patterns, and CQRS via MediatR.
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 code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.
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。
Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection 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。
Generate 3-5 lead magnet ideas from the brand's assets, graded by effort and power. "what should we give away"
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。
Run fable-mode execution discipline on Claude Fable 5.1 — the top of the escalation ladder and the strongest staged run available. Routes the task to the @fable-orchestrator agent with its model overridden to Fable (`model: "fable"`), which stages the work, delegates artifact production to @fable-worker-sonnet / @fable-worker-haiku, and cold-checks deliverables with @fable-verifier. Trigger when the user explicitly asks for thorough/systematic/"deep work" handling on the strongest model ("fable on fable", "stage this on fable", "deep work mode, fable", "run this on 5.1"), or when a fable-opus run reports the task exceeds Opus's ceiling. Benchmarked 2026-09-02: zero correctness delta on Fable 5.1 at ~1.1× tokens, ~2× wall — a provenance runner, not an accuracy runner. Do NOT use for ordinary single-pass tasks — prefer fable-opus, fable-sonnet, or fable-haiku when the task doesn't need peak reasoning. Fable is plan-included; bulk work still routes down-tier.
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 pulsing neural network — an AI backdrop. A bold, canvas-based effect from Open Design's html-ppt fx pack — for slides and launch videos. Guards prefers-reduced-motion (does not start). One per screen; on web use sparingly.
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,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers.
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 PCI DSS compliance advisor covering PCI DSS v4.0.1 (current) and v4.0. Use this skill whenever a user asks about PCI DSS, payment card security, cardholder data protection, CDE scoping, SAQ types (A, A-EP, B, B-IP, C, C-VT, P2PE, D), ROC, AOC, QSA assessments, ASV scans, merchant levels, service provider levels, network segmentation, penetration testing, tokenisation, encryption of PAN data, or any of the 12 PCI DSS requirements. Also trigger for questions like "are we PCI compliant?", "how do I scope my CDE?", "which SAQ applies to us?", "what changed in PCI DSS v4.0?", "how do I prepare for a QSA audit?", or any request involving payment data security, cardholder data environment, or PCI certification readiness.
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。
Argentine Supreme Court citation network analysis using JurisRank — a peer-reviewed PageRank algorithm with temporal decay for measuring jurisprudential authority. Ranks precedents by citation influence, traces doctrinal evolution, and detects constitutional drift. Published methodology: JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Activate with: which cases to cite, rank precedents, case authority, doctrinal evolution, Argentine Supreme Court, CSJN jurisprudence, citation network, leading case, legal research Argentina.
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。
WS-Discovery protocol scanner for discovering and enumerating ONVIF cameras and IoT devices on the network. Use when you need to discover ONVIF devices, cameras, or WS-Discovery enabled equipment on a network.
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 testing decision trees for GdUnit4: unit vs scene vs CI gates, headless runners, snapshots, and mock networks. Use when choosing test layers, wiring CI, or validating signals/physics without beginner assert catalogs. Keywords: GdUnit4, GdUnitTestSuite, headless CI, snapshot test, mock network, scene integration test, TDD.
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 fighting games including frame data (startup/active/recovery frames, advantage on hit/block), hitbox/hurtbox systems, input buffering (5-10 frames), motion input detection (QCF, DP), combo systems (damage scaling, cancel hierarchy), character states (idle/attacking/hitstun/blockstun), and rollback netcode. Based on FGC competitive design. Trigger keywords: fighting_game, frame_data, hitbox_hurtbox, input_buffer, motion_inputs, combo_system, rollback_netcode, cancel_system, advantage_frames.
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 Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.
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 patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, rollback.
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。