「stack」の検索結果

World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and modern data stack. Includes data modeling, pipeline orchestration, data quality, streaming quality monitoring, and DataOps. Use when designing data architectures, building batch or streaming data pipelines, optimizing data workflows, or implementing data governance.

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Implement paper-defined attention variants by extracting mechanism invariants, mapping tensor shapes, preserving module interfaces, validating numerical behavior, and integrating the custom attention into an existing transformer stack.

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 technical architecture, select technology stack, and define implementation strategy from specifications and constitution constraints.

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。

Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.

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 hybrid cloud architect specializing in complex multi-cloud solutions across AWS/Azure/GCP and private clouds (OpenStack/VMware). Masters hybrid connectivity, workload placement optimization, edge computing, and cross-cloud automation. Handles compliance, cost optimization, disaster recovery, and migration strategies. Use PROACTIVELY for hybrid architecture, multi-cloud strategy, or complex infrastructure integration.

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。

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

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Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.

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 this skill when working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md, and workflow.md 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。

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.

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。

Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.

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 errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

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。

Smallest personal narrated-explainer-video pipeline (spoken narration over visuals, not an audio podcast), fully tool-agnostic and autonomous by default — topic → research ∥ asset collection → script → TTS → video → 4K render ∥ publish info + cover. The skill defines the pipeline logic and self-verified checkpoints; any TTS backend and any video tool (Remotion, HyperFrames, CapCut, ...) work, and how much human oversight to apply is set by the working project's AGENTS.md/CLAUDE.md, not here. Use when the user wants a quick personal narrated video with minimal steps, whether or not they name the tool stack. Do NOT trigger for audio-only podcasts, written episodic content, or heavy multi-format production.

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。

Automates interactions for Apple-platform apps (iOS, tvOS, macOS) and Android devices. Use when navigating apps, taking snapshots/screenshots, tapping, typing, scrolling, or extracting UI info across mobile, TV, and desktop targets.

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Scaffolds React Native libraries with create-react-native-library for standalone libraries or local native modules and views. Use when creating or working on React Native libraries or adding native functionality in an existing app.

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Reviews React Native TV apps for focus/D-pad navigation, 10-foot UI layout, TV playback/DRM integration, low-memory TV performance, and TV accessibility. Use when building, debugging, or reviewing react-native-tvos, Expo TV, Amazon Vega/Kepler, or React Native web TV targets where the issue depends on remote input, TV focus, TV packaging, TV hardware, or TV playback constraints.

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Upgrades React Native apps to newer versions by applying rn-diff-purge template diffs, updating package.json dependencies, migrating native iOS and Android configuration, resolving CocoaPods and Gradle changes, and handling breaking API updates. Use when upgrading React Native, bumping RN version, updating from RN 0.x to 0.y, or migrating Expo SDK alongside a React Native upgrade.

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Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", or "test this app" on mobile. Produces a structured report with reproducible evidence: screenshots, optional repro videos, and detailed steps for every issue.

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Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.

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House style for user-facing documentation — voice, scope, structure, and what to leave out. Use this skill whenever writing, editing, or reviewing anything a user reads to learn how to use a tool — help center articles, getting-started guides, tutorials, feature docs, README usage sections, in-app help, release notes, or FAQ entries. Trigger it even when the request is phrased plainly — "document this feature", "write docs for X", "explain this to users", "write a README for this library", "turn these notes into a guide" — and even when no style guidelines are mentioned. Also use it to review existing docs for tone, bloat, or leaked implementation detail. Do not use it for internal engineering docs, architecture write-ups, RFCs, or code comments.

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。

Validates skills in this repo against agentskills.io spec and Claude Code best practices. Use via /validate-skills command.

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。

GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub API.

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Write tests using React Native Testing Library (RNTL) v13 and v14 (`@testing-library/react-native`). Use when writing, reviewing, or fixing React Native component tests. Covers: render, screen, queries (getBy/getAllBy/queryBy/findBy), Jest matchers, userEvent, fireEvent, waitFor, and async patterns. Supports v13 (React 18, sync render) and v14 (React 19+, async render). Triggers on: test files for React Native components, RNTL imports, mentions of "testing library", "write tests", "component tests", or "RNTL".

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。

Assesses whether and how an existing mobile product should migrate to React Native. Use when auditing one or more product repositories for migration readiness, including products whose iOS, Android, and other clients live in separate directories or repositories; choosing brownfield, greenfield, or a checkpoint-based path; defining a representative trial; or preparing a baseline and ROI decision before implementation. When product scope or material evidence is unavailable, grills the stakeholder with exactly one question per turn instead of sending a questionnaire.

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Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt / environment.yml / uv.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block. Use when user says "capture the environment", "snapshot my dependencies", "pin the versions", "make a renv.lock / requirements.txt", "make this byte-reproducible", or before releasing a replication package to openICPSR / the AEA Data Editor.

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。