6,714 件 ・ 関連度順
概要と使いどころ
Detects Vitest test-isolation hazards: unrestored vi.spyOn/vi.mock without afterEach cleanup or restoreMocks config, un-awaited resolves/rejects assertions, and shared mutable module state across tests.
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Checks Next.js Server Actions ('use server') for missing authentication/authorization before mutations, missing input validation, and untrusted client-supplied IDs — treating each action as a public HTTP endpoint.
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。
App Router の Server Component でクライアント専用APIを使っていないか確認する。
Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native 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。
Self-verification loop. After completing a task, re-read the original request, list each requirement, verify whether it was met, and fix gaps before stopping.
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。
Bootstrap an AI-agent skill from a TypeScript codebase by running the deterministic skillit generate/audit loop and enriching repo source (JSDoc, README, config-type properties, MCP tool annotations, examples, package.json) until the skill reaches its grade target. Use for cli, typedoc, config, or mcp (build-mode) projects; never edit SKILL.md/references directly.
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 an Estuary derivation that continuously aggregates metrics (daily totals, running counts, min/max, lifetime revenue) using reduction annotations. Use for real-time dashboards, continuous materialised views, and replacing batch ETL aggregations with streaming. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "aggregation derivation", "derivation to sum daily totals", "running-count derivation", "transformation for min/max per group", "derive lifetime metrics", "aggregate-by-date derivation", or "real-time-dashboard derivation".
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 an Estuary derivation with custom SQLite state (internal tables) to make per-document decisions based on accumulated history — account balances, inventory levels, approval workflows, deduplication. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "stateful derivation", "derivation to track balance", "transformation to approve based on state", "derive an approval workflow", "deduplication derivation", or "build a stateful derivation".
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 an Estuary derivation for stateless filtering, field selection, and per-document field transformation. Use for WHERE clauses, projecting fields, computing new fields from existing ones, or data cleansing. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (renaming alone is usually a projection, not a derivation). Use when user says "filter-transform derivation", "derivation to filter by status", "transformation with WHERE clause", "derive computed fields", "cleanse data with a derivation", or "stateless derivation".
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 an Estuary derivation that flattens a nested array into one output document per array element. Use for normalising nested JSON, exploding line items, unpacking tags, or producing one-row-per-item tables from arrays. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (some destinations can `UNNEST` server-side without one). Use when user says "flatten-array derivation", "derivation to explode an array", "transformation to unnest", "derive one row per item", or "flatten nested data with a derivation".
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 an Estuary derivation that maintains a sliding time window of events (e.g. "transfers in the last 24h", "failed logins in the last 5 minutes") using internal SQLite state and readDelay for time-based expiration. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "windowing derivation", "derivation for last-24h events", "rolling-window derivation", "sliding-window transformation", "fraud-detection derivation", "rate-limit derivation", or "time-window derivation".
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 an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".
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。
Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.
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。
Generative UI (GenUI) for Flutter using AI models like Google Gemini, Anthropic Claude, or OpenAI via the genui package. Use this skill when building dynamic AI-driven interfaces, conversational UI flows, server-rendered screen layouts, LLM-powered dashboards, chat-based UI generation, or implementing prompt-to-UI systems. Supports AI-generated widgets, reactive data binding, ContentGenerator integration, and A2uiMessageProcessor for real-time UI updates from AI responses. Ideal for apps where UI structure is determined by AI/LLM output rather than hardcoded layouts.
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。
State management architecture for Flutter using Riverpod, Provider, and BLoC patterns. Use when choosing a state solution, implementing reactive state, resolving rebuild issues, or structuring MVVM/BLoC architecture.
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Inspect, debug, and inject custom code into a running Steam client — desktop (macOS, Linux, Windows) or Steam Deck over the network — through its Chromium Embedded Framework (CEF) Chrome DevTools Protocol endpoint. Use when developing Steam UI plugins, mods, themes, or integrations — injecting CSS/JS to try a change, locating webpack modules and obfuscated class names, reading React or SteamUIStore state, inspecting Big Picture / Quick Access Menu windows, screenshotting what actually rendered, streaming console logs, or diagnosing runtime errors in Steam's UI. The same commands run against either device, or both at once. Injection is per-session and for development only. Not for building a plugin loader or making changes persist across restarts, Steamworks game SDK work, game development, or scraping the public Steam web store.
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。
Reviews mobile code for production bugs across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform, including KMP source-set and host API contracts. Covers lifecycle, concurrency, UI state and native boundaries with file:line evidence. Use for a code review, PR, project audit, quality check or /reis-mobile:review.
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。
Reviews mobile security across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform using OWASP MASVS. Covers credential storage, secrets, transport, deep links, WebViews, logging and platform implementations of shared KMP contracts. Use for security audits, auth/token handling, pentest findings or release hardening.
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。
Prepares mobile releases across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform, including separate Android/iOS artifacts from a shared KMP revision. Covers versions, signing, symbols, store readiness, rollout, release notes and CI/CD. Use for release audits, store submission, build pipelines or rollout planning.
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。
Integrates and reviews Firebase across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers Auth, databases, Storage, Functions, FCM, Analytics, Crashlytics, Remote Config, App Check and KMP shared-to-platform SDK boundaries. Use for any Firebase setup, bug, security rule, emulator, configuration file or product 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。
Designs and reviews offline-first mobile data on every stack — Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers the local store, the outbox of pending mutations, idempotency keys, retry and backoff, conflict resolution, reconnection, and how to test a flaky network deterministically. Use when an app must work without connectivity, when writes are lost or duplicated after reconnecting, or when local and server data disagree.
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。
Audits and fixes mobile accessibility across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform, including shared Compose UI and native hosts. Covers TalkBack/VoiceOver labels, roles, state, reading order, touch targets, text scaling, contrast and focus. Use for a11y audits, screen-reader bugs or accessible UI 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。
Designs and reviews mobile architecture across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers state ownership, data flow, modules, dependency boundaries, navigation, offline data and KMP shared source sets versus host apps. Use when structuring a feature, choosing state management, refactoring layers or deciding where a real class or screen belongs.
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。
Writes, runs and reviews mobile tests across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers Dart widget/integration tests, JUnit/Compose/Espresso, XCTest/XCUITest, Jest/Detox, and KMP common/target tests. Use to add, fix, run or audit tests, test setup, mocks, coverage and flaky tests for a real app 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。