8,904 件 ・ 関連度順
概要と使いどころ
Design and configure model serving infrastructure — endpoint scaling, batching, GPU allocation. Use when asked to "serve this model", "design an inference endpoint", or "size GPU allocation for serving".
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。
Ultimate production readiness skill that orchestrates all relevant skills (frontend, backend, security, performance, SEO, testing, DevOps) to harden applications before deployment / Skill kesiapan produksi utama yang mengorkestrasi semua skill relevan (frontend, backend, keamanan, performa, SEO, testing, DevOps) untuk mengeraskan aplikasi sebelum deployment.
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 guide for continuous integration, deployment pipelines, Docker, Kubernetes, and Infrastructure as Code (IaC) / Panduan ahli untuk CI/CD dan infrastruktur.
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。
Power Platform ソリューションの全体アーキテクチャを設計する。Copilot Studio / Power Automate / Code Apps / Copilot Managed Runtime / Power Pages / AI Builder の使い分け判断、コンポーネント選定、統合パターンを決定する。社内向け画面は利用者のライセンス（Power Apps Premium か、Copilot Credits の従量課金か）と利用頻度をヒアリングし、Code Apps と Copilot Managed Runtime を使い分ける。構成が確定したら、実装着手前に admin スキルで環境チェック（既定環境ではないか・マネージド環境・Code Apps / MCP の有効化・セキュリティ ロール）と DLP 事前チェック（使用コネクタがブロックされていないか・Business / Non-business が混在しないか）を実行して結果をユーザーに提示する。Agent 365 の AI チームメイトを採用する場合はライト実装（PoC）と本格実装（private リポジトリ + CI/CD + Agent Evals）を AskUserQuestion で選ばせ、Git ホスティング（GitHub / Azure DevOps Repos / その他）も確定してから実装へ進む。外部の文章を読むエージェントではプロンプト インジェクション対策を設計段階で工数に含める。
PMU observation pattern for agent health monitoring. Runs patrol loops, detects stalled agents, sends nudges, and escalates persistent failures to the mayor. Never modifies agent work or resolves conflicts.
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。
Kolla-Ansible day-2 operations skill for post-deployment infrastructure lifecycle management. Covers service reconfiguration (globals.yml changes, config overrides, prechecks, targeted reconfigure with --tags), minor and major OpenStack upgrades (image pull, upgrade procedure, rollback), container management (restart, logs, health inspection), maintenance mode (compute disable, instance drain, host maintenance), password rotation, certificate renewal, and rolling updates. This skill is for operations after initial deployment -- the kolla-ansible deployment skill covers initial bootstrap and deploy.
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。
Guidance for writing OpenStack operations manual procedures following NASA document standards. Use when authoring per-service procedures, maintenance workflows, or operational documentation that must be verified against running infrastructure.
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。
Identify and annotate cloud cost implications of architectural decisions. Use when reviewing infrastructure changes or designing new services.
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 comprehensive guide for using ConfigHub to manage Kubernetes configuration across multiple environments using Configuration as Data principles. This rulebook covers installation, configuration management, variant handling, and operational workflows.
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 creating, grooming, planning, or closing a backlog item. Bridges backlog items to SAM planning with issue, project, and milestone tracking against the configured backend. Activates on interactive browsing with no arguments, loading an item by issue reference or title match to run grooming and SAM planning, autonomous unattended runs that substitute evidence-derived decisions for clarifying questions, a quick path for one-file fixes where full grooming is disproportionate, dismissing an item without completion under a required reason (duplicate, out of scope, superseded, wontfix, blocked), marking an item done with an evidence trail and required summary, or initializing GitHub tracking infrastructure for a project. Stops when the item already has a plan or is blocked on missing information.
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 finding real role-holders at known company domains from an ICP, especially prompts like 'find all job titles at these companies', 'find qualified titles', 'find RevOps or marketing-ops buyers', or when exact title discovery should precede paid people search.
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。
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
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 a product messaging library from your positioning, your website and customer evidence: a description, the status quo and alternatives, pain points with their knock-on consequences, capabilities, functional, emotional and social benefits, branded features, the cost of doing nothing, common objections with responses, and core messaging blocks (tagline, elevator pitch, value props, proof, per-audience lines). Every claim sourced. Triggers: "product messaging", "messaging library", "messaging framework", "value props", "capabilities and benefits", "what are our differentiators in words". Run after /positioning. Not for choosing the position itself (use /positioning).
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 L&D framework for upskilling DevOps/IaC/Automation teams to become AI Agent Engineers. Covers LLM literacy, RAG, agent frameworks, multi-agent systems, and LLMOps. Designed to help traditional automation teams compete with OpenAI and Anthropic.
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 and operate multi-agent orchestration patterns (ReAct loops, evaluator-optimizer, orchestrator-workers, tool routing) for LLM systems. Use when building or debugging agent workflows, tool-use loops, or multi-step task delegation; triggers: agentic, multi-agent, orchestration, ReAct, evaluator-optimizer, tool-use, handoff.
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 AgentOps into a new or existing project. Handles .agent/ setup and .github/ merging.
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 clean git branches from feature work, excluding agent-ops files. Use for PR preparation.
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 new AgentOps skills via interactive interview. Supports from-scratch and clone modes with tiered complexity.
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。
Automatic init the first time Claude acts in an incident or alerts channel — one named like #inc-…, #incident-…, #sev0-…/#sev1-…, or whose recent messages are pages or alerts from PagerDuty, Opsgenie, incident.io, Datadog, Sentry or Grafana, or relayed by people (talk about being paged is not an alert) — that isn't already a team's oncall / monitoring channel. Run once per channel, on first contact (just invited, first @-mention, channel just created), before doing what was asked: load the oncall memory oncall setup wrote to shared workspace memory, pick the owning team's section, work out which monitoring / paging / code tools Claude can reach and which are missing, post one short zero-context message, note findings in this channel's memory, then hand off to `incident-investigate` if something was asked — or immediately, unasked, when the channel was plainly opened for a live outage. Works with no oncall memory (offers setup once). Also on "load the oncall setup here" / "init this incident".
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 whenever the user wants to find, shortlist, vet, or enrich US software development firms — custom software, web development, mobile app development, backend/API development, DevOps/cloud, system integration, and hosting. Triggers on "find a software dev shop in Austin", "shortlist three custom-software firms with healthcare experience", "we need a mobile app developer for our iOS launch", or "pull contact info for these 10 dev shop domains", even when described indirectly (build a tool, ship a feature, technical partner). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-web-developer for strictly website/landing-page projects. Defer AI/ML, ML pipelines, model building, and data-engineering asks — those are a sibling industry, not software development. Skip in-house engineer hires, code-writing/debugging tasks, cloud-product comparisons, hardware/civil engineering, non-US firms, individual freelancers.
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 whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.
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。
Kubernetes best practices: security, workloads, networking, config, operations, GitOps. Use when writing or reviewing K8s manifests and configurations.
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。
GCP best practices: IAM, secrets, networking, security, compute, IaC, ops. Use when building, reviewing, or modifying GCP 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。
AWS best practices: IAM, secrets, networking, security, compute, IaC, ops. Use when building, reviewing, or modifying AWS 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。