2,517 件 ・ 関連度順
概要と使いどころ
Add PostHog error tracking to capture and monitor exceptions. Use after implementing features or reviewing PRs to ensure errors are tracked with stack traces and source maps. Also handles initial PostHog SDK setup if not yet installed.
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。
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
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。
Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey completeness, then summarizes the pre-error context. Replaces blind session picking from potentially hundreds of linked recordings.
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。
Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.
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。
Publication-quality physics plots — vector fields, streamlines, contour maps, 3D surfaces, phase space, spectrograms, and animations. Optimized for journal submission with LaTeX labels, proper colormaps, and multi-panel 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。
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。
Meta-skill — browse and discover all installed stellar.new skills. Use when a user says "what skills do I have", "show me available skills", "what can I do", "find a skill for X", "which skill should I use", "help me navigate", "what does stellar.new do", or "where do I start". Lists skills by journey phase, surfaces the SKILL_ROUTER trigger phrases, and recommends the next skill given current 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。
Builds production-quality, accessible, responsive user-facing UIs. Use when building or modifying interfaces and pages, creating components, implementing layouts, meeting WCAG accessibility requirements, managing state, or when the output needs to look and feel production-quality rather than AI-generated.
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。
TypeScript and test style conventions for the testmex monorepo. Use when writing or reviewing TypeScript types, interfaces, core domain models, or tests in this repository.
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。
Name C# symbols, events, prototypes, FTL keys, resources, and compatibility surfaces consistently.
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 marketplaces for AI models and prompts. TRIGGERS - Use when user needs help with ai-marketplace-builder related tasks.
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。
Enhanced architecture guidance for voice-first Brazilian fintech applications. Use when designing voice interfaces, implementing PIX/Boletos, optimizing financial systems, or making technology stack decisions for Brazilian market applications. Integrates with docs/ content, MCP tools for Brazilian market research, enhanced validation scripts, and comprehensive Brazilian compliance patterns.
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。
Validate digital outputs for compliance with accessibility standards (e.g., WCAG, Section 508). Use when reviewing reports, dashboards, documents, or interfaces from pilot projects to identify and remediate accessibility barriers.
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。
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
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 aoa-safe-infra-change workflow inside an abyss-* repository using repo-relative operational surfaces, explicit local authority notes, rollback posture, and local validation commands. Use when the base infra-change workflow is correct but a thin project overlay is needed for one abyss repo. Do not use when the base skill is sufficient without local adaptation or when the task is really about producing a shareable artifact.
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。
Claude Code (code.claude.com) の各サーフェス（Desktop / IDE / Web / モバイル / ターミナル UX）リファレンス。 Desktop app（launch.json, scheduled tasks, WSL, Linux, iOS simulator）、 VS Code / JetBrains / Chrome 拡張連携、claude.ai/code（Web）と mobile アプリ、 interactive mode, fullscreen, voice dictation, accessibility, computer use, artifacts。
Unity 6 UI development guide. Use when building user interfaces, menus, HUD, buttons, or any UI elements. Covers UI Toolkit (recommended for new projects — USS, UXML, UI Builder, data binding), uGUI/Canvas (legacy runtime UI), and IMGUI. Based on Unity 6.3 LTS documentation.
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。
Read current Unity Console entries from a running Editor. Use during bug investigation after compile, tests, PlayMode, or dynamic code to inspect logs, warnings, errors, and stack traces.
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。
Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".
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-level browser control for UI that snapshots, refs, and locators cannot target - canvas apps, extension popups, OS-drawn dialogs, custom drag surfaces. Read this when a DOM-targeted action fails twice, when the next decision depends on rendered pixels, or when CUA clicks land on the wrong element.
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。
Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.
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。
Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.
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。