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概要と使いどころ
Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming. Prevents 11 documented errors. Use when: building agents with tools, voice agents with WebRTC, multi-agent workflows, or troubleshooting MaxTurnsExceededError, tool call failures, reasoning defaults, JSON output leaks.
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 linked docs drift, when a source file changes and downstream PRDs, decks, or notes must follow, or when a .sync-report.md exists. Diffs the proposed edits, applies them only after approval, and never overwrites a target file.
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 committed feature-branch changes through the no-mistakes pipeline: intent, rebase, review, test, docs, lint, push, PR, and CI. Use when the user asks to run no-mistakes, ship safely, validate before pushing, or gate a change before it reaches upstream.
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。
Standards for Feign clients and asynchronous messaging with Spring Cloud Stream. Use when implementing Feign HTTP clients or async event messaging in Spring Boot microservices.
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。
Select and implement SSG, SSR, ISR, Streaming, or Partial Prerendering strategies in Next.js App Router. Use when choosing a rendering mode for a page, configuring generateStaticParams, or enabling PPR.
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。
Inspect LiveView socket assigns for memory bloat — missing temporary_assigns, unused assigns, unbounded lists needing streams, memory estimates. Use when LiveView memory grows or you need to add temporary_assigns.
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 LiveView: async data (assign_async), PubSub (check connected?), phx-change events, form components/modals/uploads, streams for lists, live_patch. Use when handling interactions, debugging events, or tracking Presence.
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。
Inspect LiveView socket assigns for memory bloat — missing temporary_assigns, unused assigns, unbounded lists needing streams, memory estimates. Use when LiveView memory grows or you need to add temporary_assigns.
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。
Guides audio mastering for streaming platforms including loudness optimization and tonal balance. Use when the user has approved tracks and wants to master audio files.
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。
Copies track content (lyrics, style prompts, streaming lyrics) to the system clipboard. Use when the user needs to paste lyrics or style prompts into Suno or other external tools.
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。
Stages and commits the current changes onto a safe working branch, enforcing branch discipline and optionally pushing upstream. TRIGGER when: the user wants to commit, save, or check in the current changes. DO NOT TRIGGER when: opening a pull request → pr.
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。
Rebases a feature branch onto its latest base, resolving conflicts while preserving the intent of local changes, optionally force-pushing and watching CI afterward. TRIGGER when: the user wants to rebase a feature branch, update a branch against its base, or replay local work on top of the latest upstream. DO NOT TRIGGER when: merging a release branch into dev → merging-branches; only watching CI on an already-open PR → monitoring-pull-requests.
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。
SwiftUI view composition, @Observable patterns, async/await concurrency, TCA architecture, and Combine reactive streams.
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。
React Server Components, Suspense boundaries, streaming SSR, partial prerendering patterns for Next.js App Router.
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。
Document modeling, aggregation pipeline, indexing strategy, change streams, and multi-document transactions.
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。
Protobuf schema design, streaming patterns, interceptor chains, deadline propagation, and error handling for gRPC 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。
Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.
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。
ETL/ELT patterns, batch vs streaming, idempotency, data quality framework, and pipeline orchestration
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。
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming 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。
Implements media and file management components including file upload (drag-drop, multi-file, resumable), image galleries (lightbox, carousel, masonry), video players (custom controls, captions, adaptive streaming), audio players (waveform, playlists), document viewers (PDF, Office), and optimization strategies (compression, responsive images, lazy loading, CDN). Use when handling files, displaying media, or building rich content experiences.
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。
Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases. Use when importing CSV/JSON/Parquet files, pulling from S3/GCS buckets, consuming API feeds, or building ETL pipelines.
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。
Normalize cross-skill JSONL interfaces (ids + titles + citation key formats) so downstream skills do not rely on best-effort joins.
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。
Evidence self-loop for surveys: read evidence bindings + evidence packs, then write an actionable upstream TODO plan (which stage/skill to fix) before writing more prose.
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。
Automatically fix broken OpenCLI adapters when commands fail. Load this skill when an opencli command fails — it guides you through collecting a trace artifact, patching the adapter, retrying, and filing an upstream GitHub issue after a verified fix. Works with any AI agent.
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。