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概要と使いどころ
Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.
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。
OpenCTI is an open-source platform for managing cyber threat intelligence knowledge, built on STIX 2.1 as its native data model. This skill covers building an automated IOC enrichment pipeline using O
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 implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.
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。
Unified document optimization skill that chains docling-converter, imagemagick-expert, and markdown-to-pdf. Automatically detects input format, applies appropriate conversion pipeline, optimizes embedded images, and produces web/print-ready output with configurable quality presets. Use when converting documents through multi-step pipelines, optimizing PDF images, creating print-ready documents from various sources, or batch processing documents with image optimization.
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。
DuckDBを使用した大規模データ分析の専門スキル。DuckDBのアーキテクチャ、SQL構文、パフォーマンス最適化、各種ファイル形式（CSV、Parquet、JSON等）の効率的な読み込み・書き出しを熟知。メモリ効率の良い分析、複雑なクエリの最適化、データパイプライン構築を支援。Use when analyzing large datasets, querying CSV/Parquet/JSON files directly, building data pipelines, or optimizing analytical queries with DuckDB.
METAINFORMANT rules for directory scripts/gwas/pipelines. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
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。
Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload 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。
End-to-end data pipeline for empirical research: fetch economic data from APIs (FRED, World Bank, IMF, BLS, OECD, Yahoo Finance), clean and transform raw data, construct strategy-specific variables, and validate panel structure. Use when asked to fetch data, download data, clean data, merge datasets, prepare analysis-ready data.
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 CI/CD checks until green or failure with auto-diagnosis, failure classification (related vs flaky vs external), self-healing fix attempts, and smart retriggers for flaky E2E tests. Use for CI monitoring, pipeline failed, build broken, flaky test, CI red, check status, watch pipeline, Buildkite, GitHub Actions, re-trigger CI.
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。
Project-first Research pipeline with live gates, source/PDF evidence, claim boundaries, compute and publication controls; includes an optional PubMed/arXiv standard-library helper.
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。
Automated software development pipeline. Scans projects, prioritizes tasks, analyzes code, and orchestrates development loops. Zero dependencies (Python stdlib only).
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 a shareable recap of selected Screenpipe activity while minimizing private details.
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 a past decision, document, or conversation in Screenpipe with source links.
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。
Query the user's local and synced-device data via the screenpipe REST API at localhost:3030 — recordings, audio, UI, meetings, connected services, and memory. Use for screen activity, other-device or cross-device history, productivity, media export, connections, durable memory, or discovering and automating saved 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。
Agentic design-to-build pipeline that turns a Figma design into a built WordPress site using the Figma MCP server (read side) and the Elementor MCP server (write side) attached as MCP Apps on an NV oOS assistant. Covers the 7-stage pipeline (Scope → Read → Plan → Tokenize → Build → Verify → Handoff), the normative stage rules (get_design_context first, tokenize before build, drafts only, never publish, Figma read-only), the build-manifest contract (schema + example in reference/build-manifest.md), the design-file contract (frame/section/variable naming in reference/design-file-contract.md), assistant wiring (figma + elementor MCP Apps, OAuth + application passwords, host allowlist), safety rules, and troubleshooting. Use when asked to build or create a site, page, or landing page from a Figma design, to wire Figma MCP or Elementor MCP for design-to-build work, to approve or produce a build manifest, or to debug a failed design-to-build run.
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 execute DAG-based automation workflows using the NV oOS Pro Workflow Builder — a ReactFlow visual builder for chaining tool calls, agent runs, and actions into repeatable pipelines. Covers the visual builder UI, 9 preset categories, 10 node types, Kahn's algorithm execution engine, scheduling via Pro Schedule Manager, template variable syntax, and best practices. Use when designing workflows, debugging DAG execution failures, choosing between a workflow schedule and raw tool chaining, or building CRM/PM automation pipelines with toolkit_cpt nodes.
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 the NV oOS Pro Toolkit CRM — leads, deals, companies, contacts, customers, activities, and support tickets. Covers the complete sales pipeline from lead capture through qualification, deal management, and post-conversion customer tracking with BANT/MEDDIC scoring, activity logging, and workflow automation. Use when working with CRM records, managing pipeline stages, qualifying leads, creating company profiles, logging calls/emails/meetings, or troubleshooting CRM data issues.
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 execute DAG-based automation workflows using the NV oOS Pro Workflow Builder — a ReactFlow visual builder for chaining tool calls, agent runs, and actions into repeatable pipelines. Covers the visual builder UI, 10 preset categories (incl. AI Fashion Production, v1.1.92+), 10 node types, Kahn's algorithm execution engine, scheduling via Pro Schedule Manager, template variable syntax, and best practices. Use when designing workflows, debugging DAG execution failures, choosing between a workflow schedule and raw tool chaining, or building CRM/PM automation pipelines with toolkit_cpt nodes.
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。
Automate Apipie AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
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-to-end Android APK red-team pipeline
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。
Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.
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。
Field marketing, events, and webinars for B2B SaaS. Use this skill for conference and sponsorship selection, booth strategy, owned events and roadshows, executive dinners, the webinar program, and event-sourced pipeline measurement. Also triggers on: field marketing, events, conference, trade show, booth, sponsorship, roadshow, executive dinner, webinar, event ROI, event pipeline, user conference, meetups.
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。
Report project state and route the next stage. Use when the user says "where is my project", "what is next", or "run the pipeline".
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。
Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.