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概要と使いどころ
Extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs. Use when asked to learn preferences, mine feedback, personalize workflows, or generate team/person-specific agent guidance.
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。
Inspect a Core UI or code surface for a small number of justified motion opportunities and explicitly identify what should remain static. Use when asked what should animate, where motion would improve feedback or comprehension, how to make an interface feel more alive without over-animating it, or whether a proposed animation is worth adding. Read-only; do not use to review or fix existing motion code or to implement animations.
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。
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
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。
Tasteful, subtle web UI animation following Emil Kowalski / animations.dev principles. Use when adding or reviewing interface motion — hover and press feedback, entrances and exits, modals, toasts, menus, loading and skeleton states, staggered reveals, page or view transitions — so motion stays refined and purposeful, not decorative. Covers CSS, Web Animations, and React timing/easing. Pair with the motion skill for motion/react API specifics.
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。
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
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。
Guide to interpreting BUSCO completeness statuses: why Duplicated BUSCOs count as complete, parsing output files, computing/comparing completeness across proteomes/genomes, common counting mistakes. Use when running BUSCO QC, comparing assemblies, or reporting completeness. See also: prokka-genome-annotation for annotation workflows feeding BUSCO.
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。
Open-source bio-image data management. Use the omero-py client to connect to an OMERO server, retrieve images as numpy arrays, annotate with tags and key-value pairs, manage ROIs, and feed image data into Python analysis pipelines — programmatically, no GUI.
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。
Patterns and best practices for integrating ROS2 systems with web technologies including REST APIs, WebSocket bridges, and browser-based robot interfaces. Use this skill when building web dashboards for robots, streaming camera feeds to browsers, exposing ROS2 services as REST endpoints, or implementing bidirectional WebSocket communication between web UIs and ROS2 nodes. Trigger whenever the user mentions rosbridge, rosbridge_suite, roslibjs, FastAPI with ROS2, Flask with rclpy, WebSocket for robot telemetry, MJPEG streaming, WebRTC for robots, REST API wrapping ROS2 services, web-based robot control, browser robot interface, robot dashboard, CORS configuration for robots, or any web-to-ROS2 bridge pattern. Also trigger for authentication on robot web interfaces, rate limiting sensor streams, video streaming from robot cameras to browsers, or running async web frameworks alongside the ROS2 executor. Covers rosbridge_suite, FastAPI, Flask, WebSocket, and WebRTC approaches.
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。
Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.
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 swift-snapshot-testing to visually verify SwiftUI views during implementation. Renders views to PNG for comparison against design references. Fast feedback loop (~25s/cycle).
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。
When the user asks for a code review, shares code for feedback, or says "review this", "check my code", "what's wrong with this". Also activate when reviewing a pull request or diff.
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 design for construction: text-to-BIM concepts, option generation, and AI-assisted design iteration with cost and carbon feedback. Use when exploring early design options with AI.
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。
MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimize_prompts() with GEPA for automated prompt improvement.
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。
Push records from apps, services, devices, or scripts directly into Unity Catalog Delta tables with Zerobus Ingest: SDKs (Python, TypeScript, Go, Java, Rust, C++, .NET), REST, OTLP, MQTT, Arrow Flight, or Apache Kafka-compatible producer APIs, with no message bus to run. Use to stream events, telemetry, logs, IoT data, CDC, or columnar batches into Databricks in near real time; connect existing collectors and log shippers (OpenTelemetry, Debezium, Vector, Telegraf, Cribl); replace a message bus that only feeds the lakehouse; or debug Zerobus auth, schema, throughput, or delivery 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。
Reviews pitch decks and investor presentations. Reads slide content, evaluates narrative flow, problem/solution clarity, market sizing, competitive positioning, financial projections, team credibility, and ask clarity. Generates a scored pitch-review.md with slide-by-slide feedback, overall score, top improvements, investor objection predictions, and comparisons to successful decks. Use when reviewing fundraising materials, investor decks, or pitch presentations.
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 job posts that make the right person apply -- real role clarity, honest selling points, salary range handling, and requirements pruned to what actually predicts success. Small businesses lose great candidates to bad posts long before the interview. Feeds cowork-hiring-screener and hiring-scorecard downstream.
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。
Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.
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。
API reference: Core Haptics. Query for CHHapticEngine, haptic patterns, tactile feedback.
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。
Improves a voice profile by learning from manual edits. Use after editing generated text to refine registers and close voice drift over time.
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 auditing marketing, messaging, offers, funnels, or content strategy. Triggers on "audit my marketing", "review my landing page", "improve my funnel", "content strategy review", "messaging review", "offer feedback", "marketing checkup", "why isn't my marketing working", "audit my brand". Works at any budget or company size.
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 Argilla 2.x for human-feedback dataset annotation, Python SDK dataset workflows, server deployment/operations, webhooks, and legacy v1/Rubrix migration.
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 verifies skilld CLI output, terminal pickers, and full-screen flows. Use for terminal colours, loading feedback, keyboard controls, layout, errors, or end-to-end CLI UX reviews.
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。
Research and advise on the best way to approach a software project, including architecture, tech stack, implementation strategy, pricing/operating-cost tradeoffs, benchmark research, and comparisons with similar real-world projects. Use before building, mid-build, or after completion when the user asks for project strategy, optimal approach, research comparables, similar projects, stack selection, vendor/service choice, repo analysis, architecture critique, implementation feedback, or a prioritized improvement plan. Avoid for narrow single-bug debugging or isolated file edits unless the user asks for broader project direction.
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。
Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions. Use for meeting retrospectives, employee work reviews, decision meetings, agenda and question design, direct feedback, meeting-quality diagnosis, or repeated low-value discussions. Preserve direct standards without taking over the worker's work or degrading the truth signal.
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。