Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
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概要と使いどころ
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
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。
Cascade merge changes through a chain of dependent branches. Use when updating stacked/chained PRs, propagating changes from a parent branch to all downstream branches, or when the user mentions "cascade merge", "propagate changes", "update dependent branches", or "merge to downstream branches".
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。
VISONSDK ドローン (54X / KF615 系) を PC から操縦・映像確認・顔追従するクライアント群。 iPhone 上の iOS アプリ (test.app) が制御サーバー (TCP 8080) と MJPEG 映像サーバー (HTTP 8081/stream) を提供し、USB 越しに iproxy で PC に転送する。「ドローンを飛ばす」「ドローン映像を見る」 「ドローンに顔を追わせる」「離陸/着陸/スティック操作」などで使う。
Team operations dashboard template — Linear/Asana-clean hybrid with sprint status hero, 4-segment progress bar, workstream cards, chronological activity stream with colored event badges, right-rail with today's schedule + team-presence + upcoming milestones. For team status snapshots, OKR reviews, "team this week" all-hands views.
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Promote QA → production by opening a PR from peterdrier/Humans:main to nobodies-collective/Humans:main with a properly-qualified commit summary. Use when the user says "PR to production", "promote to prod", "PR from origin to upstream", "prod PR", or any variation of pushing batched fork changes upstream. Always use this skill for the two-remote promotion flow even if the user doesn't say "prod" explicitly.
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。
Decompose tasks into structured, outcome-defined process entries with complexity triage. Load when user says "decompose this", "break this down", "what steps do I need", "plan this out", "what's the process for", "how do I approach this", or when any complex task needs structured execution planning. Includes a problem-understanding pass before complexity triage. Routes to `problem-to-plan` when the user needs planning deliverables (spec + plan + TODO). Does NOT replace brainstorming — brainstorming is design approval (upstream), this is execution planning (downstream).
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。
Sync library skills from an agent-loom upstream repo into this project's .agents/skills while preserving project-local and forked skills. Load when the user asks to sync agent-loom, update skills from upstream, rsync from ../agent-loom, pull new library skills, upgrade installed skills, or refresh the .agents folder without losing custom project skills. Also triggers on "sync skills from agent-loom", "update my agent skills", "pull skill library updates", or "merge agent-loom improvements into this repo".
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 real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
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 whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream 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。
Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.
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。
Node/TypeScript SDKを使用したMCPサーバーの構築 — ツール、リソース、プロンプト、Zodバリデーション、stdio vs Streamable HTTP。最新APIについてはContext7または公式MCPドキュメントを参照。
Integrate and maintain Robelest Convex Auth in apps by always checking upstream before implementation. Use when adding auth setup, updating auth wiring, migrating between upstream patterns, or troubleshooting @robelest/convex-auth behavior across projects.
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See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.
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 real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
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。
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential 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。
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration), ImageMagick (image manipulation, format conversion, batch processing, effects, composition), and RMBG (AI-powered background removal). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, removing backgrounds from images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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 with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
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。
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
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 parallel workstreams — list, create, switch, status, progress, complete, and resume
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。
Examine file system slack space, MFT entries, USN journal, and alternate data streams to recover hidden data and reconstruct file activity on NTFS volumes.
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。
Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
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 React Server Components (RSC) patterns with Next.js App Router including data fetching, streaming, selective hydration, and server/client composition. Use when users request "server components", "RSC", "Next.js app router", "server-side rendering", or "streaming".
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 backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.
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 data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).
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。