PRで未対応のまま残ったCI失敗をログと変更ファイルから分類し、再実行・コメント・対応見送りの判断と根拠をJSONにまとめるスキルです。
- PRに残ったCI失敗の仕分け
- 再実行に向く一時障害の判別
- PRの変更が失敗原因か確認
3,101 件 ・ 関連度順
概要と使いどころ
PRで未対応のまま残ったCI失敗をログと変更ファイルから分類し、再実行・コメント・対応見送りの判断と根拠をJSONにまとめるスキルです。
Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the transcript for', 'search YouTube for', 'what are the latest videos on', 'list this playlist', 'monitor this channel', or any request involving a YouTube URL, video ID, or @handle. Do NOT use for downloading video or audio files, YouTube engagement data (likes, comments), or private/age-restricted videos.
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 asks to automate browser tasks, scrape websites, fill forms, capture screenshots, extract structured data from web pages, or build web automation workflows. NOT for testing — use playwright-pro for that.
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。
Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes /cs:boardroom, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.
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 asks to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through Feynman explanation and recall. Covers quick, deep, map, Feynman, and whole-book reading modes.
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。
End-user browser automation with cmux. Use when you need to open sites, inspect or interact with browser surfaces, wait for page state, and extract data without stealing focus.
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 task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
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 tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
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。
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
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。
Planificación persistente basada en archivos para tareas multipaso de agentes de IA. Mantiene task_plan.md, findings.md y progress.md en disco; los hooks del ciclo de vida inyectan contexto seleccionado de planificación del proyecto. La recuperación automática solo lee los archivos de planificación del proyecto. session-catchup.py --metadata, solicitado de forma explícita, puede inspeccionar metadatos locales de sesiones del mismo proyecto; --replay puede emitir extractos limitados y enmarcados con nonce. El modo con gate opcional solo puede solicitar que el host continúe si este lo admite y nunca ejecuta comandos declarados en Markdown. El skill no tiene ninguna ruta de carga por red. Úsalo para investigación o trabajo que requiera 5 o más llamadas a herramientas.
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。
Localization pipeline — find hardcoded strings, extract string tables, cultural review, VO, RTL, enforce string freeze.
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。
Flat must-do/never-do rules sheet per system and layer, extracted from Accepted ADRs. ADRs explain why; this is actionable.
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。
Downloads YouTube video transcripts/subtitles and cover images by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification. Caches raw data for fast re-formatting. Use when user asks to "get YouTube transcript", "download subtitles", "get captions", "YouTube字幕", "YouTube封面", "视频封面", "video thumbnail", "video cover image", or provides a YouTube URL and wants the transcript/subtitle text or cover image extracted.
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 n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extractor — and whenever the user mentions AI agents, LLM with tools, tool calling, $fromAI, system prompts, agent memory, sessionId, structured/JSON output, output parser, RAG, vector store, a chat assistant/bot, or human-in-the-loop review. Covers Agent-vs-chain-vs-classifier choice, the model/memory/tools/outputParser slots, tool names/descriptions as prompt, structured output with autoFix, memory, RAG, human review, and chat topologies.
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 reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.
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。
Claude Skills meta-skill: extract domain material (docs/APIs/code/specs) into a reusable Skill (SKILL.md + references/scripts/assets), and refactor existing Skills for clarity, activation reliability, and quality 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。
Use when refactoring Handsontable code - applying SOLID principles, Law of Demeter, plugin extraction, performance optimization, code modernization, and API redesign with backward compatibility preservation
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。
Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.
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 guidance for deep security incident and entity investigations in Google SecOps. Use when investigating cases, analyzing entities (hosts, IPs, domains, hashes, users), extracting and searching UDM events, performing asset and user timeline analysis, and detecting lateral movement across enterprise networks. Don't use for detection rule authoring or YARA-L tuning (use secops-detection-engineering), proactive hypothesis-driven hunting (use secops-hunt), initial alert triage (use secops-triage), or basic case status updates (use secops-cases).
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。
Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to BigQuery on Google Cloud. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.
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。
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management 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。
Agentic end-to-end tests with e2e, the e2e runner. Covers scaffolding e2e.config.ts, picking the Playwright browser engine or the agent-device mobile engine, starting the app under test from the config, driving flows with agent.act, judging with agent.assert, agent.waitFor, and agent.extract, pinning values with screen, app, browser, and expect, shaping the agent (context, system prompt, tools, personas), the replay cache, the e2e CLI, reading .e2e/report.json, and bug bashes (parallel explore runs proven with repro tests). Use when a project depends on e2e, when asked for end-to-end, browser, mobile, or agentic UI tests, to bug bash or hunt for bugs, or when an e2e run fails.
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 for creating, editing, extracting, OCRing, filling, and converting PDF documents.
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。
Find and read information on the open web — fan-out web/news/finance search plus full-page fetching and source extraction. Use to answer current questions, gather and cite sources, verify a claim, or pull text from specific URLs. Triggers: 'search the web', 'look this up', 'find sources on', 'what's the latest on', 'fetch this page', 'is it true that…', 'compare X vs Y'.
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。