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Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular 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。
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings.
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。
Azure Cosmos DB JavaScript/TypeScript SDK (@azure/cosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management.
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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - 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 in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool ...
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。
Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or ...
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 FriendlyBet quality, regression risk, test plans, release readiness, version bump discipline, scoring/locking correctness, provider fallback behavior, and dirty-worktree safety. Use before shipping app code, scoring changes, migrations, sports integrations, copy updates, PWA cache changes, or any risky user-facing flow.
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。
Plan FriendlyBet ethical growth, SEO, README positioning, open-source contribution paths, self-hosting story, public trust, and discovery without ads, trackers, spam, or dark patterns. Use for repo-facing docs, growth strategy, launch positioning, SEO pages, contributor onboarding, or public messaging.
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。
Shape FriendlyBet product decisions, MVP scope, user stories, tournament flows, multi-sport expansion, pool mechanics, social competition loops, and feature prioritization. Use when planning what FriendlyBet should build, cut, sequence, or validate, especially for new sports, prediction formats, pool flows, leaderboards, sharing, or product 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。
Plan or review FriendlyBet architecture, implementation, schema, data flows, scoring, provider integrations, static/PWA behavior, Supabase/RLS impact, migrations, automation, and technical sequencing. Use when a task asks how to build, refactor, generalize, integrate, test, or safely ship FriendlyBet 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。
Author FE spec files, update indexes/tracker, run deepening and ambiguity gates, and enforce navigation completeness before plan-phase 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。
Assess pipeline layer state, detect prerequisite blockers, classify audit status, and persist remediation plan
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。
Validate sequencing and cross-layer readiness before phase slicing, including coverage and consistency hard gates
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。
Derive slices from specs, order by dependencies, write acceptance criteria with citations, and finalize phase/progress artifacts
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 database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for any database paradigm.
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。
Manage database migrations and schema versioning. Use when planning migrations, version control, rollback strategies, or data transformations for any database paradigm.
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 decomposition directory structure, IA shard skeletons, and all required layer indexes from approved decomposition plan
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 user wants to humanize text, make writing sound less like AI, or rewrite content to feel more natural. Triggers on "humanize", "make it sound natural", "too robotic", "sounds like AI", or similar. Works in Hebrew and English. Always output only the rewritten text — no explanations.
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。
Build and run the owner's self-branding system in a structured way across LinkedIn, Substack, dev.to, X, profile rewrites, recurring series, and comment strategy. Use when the owner asks for positioning, a branding plan, profile updates, content drafts, a publishing sequence, comment ideas, or help maintaining a consistent public voice. Optimize for operator credibility: specific experience, defensible numbers, concrete artifacts, and category ownership.
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 working with Chronosphere — chronosphere cloud-native observability platform for metrics, tracing, and alerting at scale. Covers PromQL-based metric queries, trace analysis, monitor management, dashboards, and control plane configuration. Use when querying Chronosphere metrics, investigating service performance, managing alerting rules, or analyzing distributed traces.
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 working with Azure Devops — azure DevOps comprehensive management. Covers pipelines, boards, repositories, artifacts, test plans, work item tracking, and release management. Use when checking pipeline status, managing work items, investigating build failures, or auditing Azure DevOps project 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。
Use when working with Azure Functions Deep — deep Azure Functions analysis covering function app inventory, trigger types, execution metrics, scaling behavior, slot deployments, application insights integration, and consumption plan cost tracking. Provides optimization guidance for cold starts and memory usage.
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 working with Apptio — apptio and Cloudability IT financial management and cloud cost optimization. Covers IT cost allocation, cloud cost analysis, benchmarking, budget forecasting, showback/chargeback reports, and technology business management. Use when managing IT financial planning, benchmarking cloud spend, or creating chargeback models.
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 working with Gcp Gke — google Kubernetes Engine cluster operations, node pool management, workload analysis, autopilot configuration, and upgrade planning via gcloud CLI.
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。