2,524 件 ・ 関連度順
概要と使いどころ
Diagnose Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix 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。
Turn the current project website into a short, polished, shareable launch video using Hyperframes. Use when someone says "/brag", "let's brag about this", "make a launch video", "turn this into a video", or wants to share what they built. Reads the project code directly — no live URL or screenshots needed.
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 a project directory or a website URL into a short, shareable launch video with music, motion, and share copy. One file, no bundled assets — built entirely by the model with the tools already on the machine. Use when someone says "/brag-slim", "let's /brag about this", "brag about a website", "make a launch video", or wants to show off what they built. If the /brag skill is also installed, let /brag handle those phrases; it hands off here on Opus 5.5.
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。
Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use improve-animations or review-animations instead.
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。
Digest of what the user's Superset agents did while they were away, sweeping workspaces, tasks, and agent terminals to report what finished, what needs review, and what's blocked. Use when the user asks "what did my agents do", "what happened while I was away", wants a standup or summary of agent work, or returns after a break.
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。
Coordinate several coding agents in parallel through Superset, each in its own workspace, with follow-ups, progress reads, dependency tracking, and structured results. Use when the user asks to delegate, parallelize, fan out, or split up coding work across agents, workspaces, or hosts, hand work between agents, or monitor workers, including "spin up agents for each of these", "run these in parallel", "what are my workers doing". Not for ordinary single-agent workspace, task, or automation management.
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。
Drive an app running on a Limrun cloud iOS simulator: launch, tap, type, read the accessibility element tree, read app logs and simulator syslog, screenshot, record video, connect the app to local services, play a video file as the camera, set the clipboard, read and write user defaults, post notifications, and run timed action chains. Use after a build (from any builder) when the user wants to see, test, or interact with their app on a simulator, or says 'show me a screenshot', 'tap', 'run the UI test', 'record a video', 'read the logs', 'connect localhost', 'reach my local server from the simulator', 'mock the camera', 'paste into the app', 'change the language', 'simulate Face ID', or 'launch on simulator'. To build the app first, use limrun-xcode-bazel (Bazel workspaces) or limrun-xcode (xcodebuild projects).
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 an iOS / Apple app on remote Xcode with `lim xcode build` instead of local xcodebuild, run project commands with `lim xcode run`, or run its XCTest suites with `lim xcode test`, from any environment (Linux, Windows, macOS, VM, container). Use for non-Bazel projects (an `.xcodeproj` / `.xcworkspace`, an XcodeGen `project.yml` with a gitignored project, React Native / Expo native build) when the user wants to build, compile, run code generation or Make targets, test, inspect build logs, reload, produce a preview build, or ship a signed device IPA. To run, tap, screenshot, or otherwise interact with the result on a simulator, use limrun-ios-simulator. For Bazel workspaces, use limrun-xcode-bazel.
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。
Spawns pedestrians that wander autonomously via WalkerAIController, and destroys them in the correct order. Pairs each walker.pedestrian.* with a controller.ai.walker, places them on the navigation mesh, and sends them to random navmesh points at walking speed. Use when the user asks to "spawn pedestrians/walkers", "add people/crowds", "make pedestrians walk around", or "remove the walkers". Reads the world settings first: if the world is already synchronous it never ticks it, and if it is asynchronous it makes it synchronous and drives the clock itself.
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 AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
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。
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
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。
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing 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。
Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with generics, interfaces, and robust error handling. Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration, CLI tools, benchmarks, or table-driven testing.
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。
Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing. Implements Prometheus/Grafana stacks, conducts load testing, performs application profiling, and plans infrastructure capacity. Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottlenecks, or forecasting capacity needs.
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 and configure Laravel 10+ applications, including creating Eloquent models and relationships, implementing Sanctum authentication, configuring Horizon queues, designing RESTful APIs with API resources, and building reactive interfaces with Livewire. Use when creating Laravel models, setting up queue workers, implementing Sanctum auth flows, building Livewire components, optimising Eloquent queries, or writing Pest/PHPUnit tests for Laravel features.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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。
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
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 and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.
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 GSD workspaces — create, list, or remove isolated workspace environments
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 matter workspaces — create, list, switch, close, or detach (practice-level). Keeps one client or engagement's context separate from every other for multi-client practitioners. Use when the user wants to open a new matter, switch matters, list matters, close/archive a matter, or work at practice-level 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。
Manage matter workspaces — create, list, switch, close, or detach the active matter (practice-level). Use when working across multiple clients or matters and you need to keep one engagement's context separate from another, or when a substantive skill needs to know which matter it's working in.
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 matter workspaces for multi-client practices — create, list, switch, close, or detach the active matter. Use when the user wants to create a new matter workspace, switch the active matter, list matters, archive a matter, or work at practice-level only without an active matter.
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 matter workspaces — new, list, switch, close, or detach (practice-level). Use when working across multiple clients or matters in private practice and you need to create, list, switch, close, or detach the active matter so context from one engagement doesn't leak into another.
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。