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概要と使いどころ
Frontend development context for the Megahub project. Use when working on the web-based IDE, Vite build system, Blockly visual programming, Web Bluetooth API integration, JavaScript frontend code, CSS/styles, UI components, or anything in the /frontend/ directory.
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。
Core firmware context for the Megahub ESP32 project. Use when working on PlatformIO configuration, build scripts, library structure, main.cpp, or general ESP32 firmware development. Covers build system, project structure, common pitfalls, and debugging.
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。
Blockly visual programming context for the Megahub project. Use when adding, modifying, or debugging custom Blockly blocks, the Lua code generator, the toolbox, block colors, or the BLOCKS.md documentation generation 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。
Code formatting and linting context for the Megahub project. Use when writing or reviewing code in C++ or JavaScript, or when running format/lint checks. Describes tool commands, style conventions, and when to apply them.
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。
Memory management and FreeRTOS context for the Megahub ESP32 project. Use when dealing with heap allocation, stack size, task creation, inter-task communication, semaphores, queues, or any ESP32 memory 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。
Checks whether AI-assisted work defines review criteria, accessible context, explicit review loop, human judgment boundary, and feedback capture before delegating to an agent.
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。
Ensure ADRs capture context, decision, alternatives, tradeoffs, and follow-ups in a way that prevents future drift.
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。
Turn brand context and a social brief into platform-aware copy, storyboard, reference frames, and video drafts without publishing them.
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。
Establish durable project context, asset roles, delivery constraints, and approval state for repeatable video work.
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。
Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a tight current-state brief. Use for 'recall my work on X', 'catch me up', 'what have I been working on', 'where did I leave off', before starting or resuming work.
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。
Integrates Sentry error tracking and performance monitoring into Flutter apps using `sentry_flutter`. Use when setting up crash reporting in Flutter, calling `SentryFlutter.init`, adding `SentryNavigatorObserver` to GoRouter, tracing HTTP requests with `sentry_dio`, capturing handled exceptions via `Sentry.captureException`, adding breadcrumbs, configuring session replay (`replay.onErrorSampleRate`), tuning `tracesSampleRate` or `profilesSampleRate`, controlling PII with `sendDefaultPii`, or setting user context after login and logout.
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。
Code-native UI design lifecycle engine (Figma alternative) with Contextual Decision Layer (CDL). Supports all 7 design stages with zero per-page CSS/JS and pluggable CSS foundations (Native, Tailwind, daisyUI, Pico, Hybrid). Trigger on commands 'brief', 'study', 'init', 'brand', 'tokens', 'palette', 'layout', 'components', 'page', 'dashboard', 'motion', 'i18n', 'audit', 'deploy', or design system 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。
Designs and reviews production observability for mobile apps on every stack — Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers crash and error reporting with usable context, breadcrumbs, structured logs, traces and custom metrics, release and cohort segmentation, correlation with backend requests, alerting thresholds, sampling and cost, and what must never be collected. Use when production problems cannot be explained from the available data, when setting up crash reporting or telemetry, or when defining release health alerts.
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 OpenAI Codex CLI as a peer collaboration partner — same standing as Claude, not a one-shot tool. Bring Codex in EARLY (ideation, framing decisions, stuck moments), not only for late peer-review. Hand it strategic context (target, research, draft, reasoning), iterate conversationally over ~3-8 turns, converge before surfacing to the human. Invoke when the user says "check / iterate / ideate with Codex" or "ask Codex" — and proactively when stuck between two reasonable framings, pressure-testing a load-bearing claim or structure, or about to ask the human to pick between options two agents could resolve.
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 tsift for token-efficient repository navigation, code search and reading, call graphs, diffs, logs, tests, session context, and workspace memory. TRIGGER: exploring or changing a codebase with tsift installed, or working on the tsift repo. SKIP: plain file-level glob, non-code web search. VERSION CHECK: compare `tsift --version` against tsift-version below before trusting any command text copied from this file.
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 you need code research over an indexed codebase with minimal context: structural graph queries (who calls X, call chains, architecture overview, dead code, cross-service HTTP routes) instead of file-by-file grep/read cycles. Also trigger to minimise token spend on repetitive code exploration.
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 in building Chrome Extensions using Manifest V3. Covers background scripts, service workers, content scripts, and cross-context communication.
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。
Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Us...
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector s...
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。
Systematic ambiguity resolution through tiered information gathering. Use when facing unclear requirements, unknown context, uncertain implementation choices, or any situation where guessing would be risky.
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。
Context-aware remapping of stale parent shard references to new sub-shard targets after shard split operations
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。
Define system architecture, error architecture, and data strategy with map guards and ideation context reload
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。
Apply the confirmed design direction to all visual surfaces. This skill now bridges the pipeline's placeholder system with the `impeccable` skill's PRODUCT.md and DESIGN.md files. If `{{DESIGN_DIRECTION}}` still appears as a literal placeholder, run `/impeccable teach` to establish design 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。