846건 · 관련도순
Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-...
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantically merge upstream kit changes while preserving project-specific values and recording sync state
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide for implementing keyboard shortcuts in React using @tanstack/react-hotkeys. Use when building hotkey/shortcut features, registering keyboard shortcuts, handling key sequences, recording custom shortcuts, tracking held keys, or formatting hotkeys for display in React applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Daily Co — daily.co video and audio API platform management for real-time video calls, rooms, recordings, and usage analytics. Use when monitoring active rooms, analyzing meeting quality, reviewing usage and billing, managing room configurations, or troubleshooting Daily.co video sessions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Read, write, and query Apple Health data using HealthKit. Covers HKHealthStore authorization, sample queries, statistics queries, statistics collection queries for charts, saving HKQuantitySample data, background delivery, workout sessions with HKWorkoutSession and HKLiveWorkoutBuilder, HKUnit, and HKQuantityTypeIdentifier values. Use when integrating with Apple Health, displaying health metrics, recording workouts, or enabling background health data delivery.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Operate desktop apps and isolated browsers on registered computers. Use for tasks that require an app interface, accessibility, screenshots or recording. Use Chromewhale for the user's signed-in Chrome.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when building or changing Skyline UI (apps/syn-ui, packages/syn-ui/*) from a design - "build this screen from the board", "implement the design", "match the canvas", "new board landed", "build the Eval trend panel", "port this screen to Skyline", "does this match the design", "update the Shipped table", "snapshot the boards". Covers reading a `*.dc.html` board and the Skyline spec, building from them, comparing 1440px and 390px screenshots against the board, and recording the shipped screen. Do NOT use for small tweaks to a screen that has already shipped (change the code directly, no board needed), for the frozen React app apps/syn-dashboard-ui (never edit it), or for refreshing the CI screenshot baselines alone (see design/README.md).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement security best practices for TwinMind integrations. Use when securing API keys, configuring privacy settings, or implementing data protection for meeting recordings. Trigger with phrases like "twinmind security", "secure twinmind", "twinmind privacy", "protect twinmind data", "twinmind api key security".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use for the infrastructure implementation phase after the backend follows the model — turning documents/infra-design decisions into infra/ (local container stack, production IaC), wiring cradle.json infra.up / infra.containers, adding IaC validate and image build steps to CI, and, once E2E passes, applying production once in a sandbox and recording it in the deployment table. Not for designing infrastructure (infra-design).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Plan, verify, and track demo/marketing video production in Busabase — idea to hook/pain-point/storyboard, codebase claim verification, recording progress, post-production handoff, and HyperFrame (Remotion) linkage. Use when the user invokes $kelly-demo-video-factory or /kelly-demo-video-factory, wants to plan a product demo video, write a storyboard, verify a video script's product claims against the codebase, track which shots are recorded, or hand a finished storyboard off to editing/Remotion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Execute a user flow step-by-step in Cursor's built-in browser while documenting each action, then emit a Playwright test that replays the same flow using stable selectors derived from the accessibility tree.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating observation volume and checking the org's monthly quota before creating, so a broad scanner doesn't exhaust the budget on its first scheduled sweep. TRIGGER when: user asks to create, set up, or configure a Replay Vision scanner, OR when you are about to call vision-scanners-create, OR when widening an existing scanner's query or sampling_rate via vision-scanners-update. DO NOT TRIGGER when: only reading scanners or observations, deleting a scanner, or running an existing scanner against a single session on demand (vision-scanners-scan-session).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Extract property ownership, legal descriptions, encumbrances, and recording details from property deeds and land registry documents.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Runs a single ScenarioRunner Python scenario (or a whole group) against a running CARLA server — FollowLeadingVehicle, ControlLoss, DynamicObjectCrossing, SignalizedJunctionLeftTurn and the rest of srunner/examples — in sync or async mode, with result output, recording and manual/agent control of the ego. Lists what is runnable on the checked-out branch and on the loaded map. Use when the user asks to "run a scenario", "test FollowLeadingVehicle", "list scenarios", "run a CARLA traffic scenario", or reports a scenario that is "not supported".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Runs the CARLA Leaderboard evaluator over a set of routes with your agent — routes/routes-subset/repetitions/track selection, checkpoint and live-results endpoints, resume after a crash, recording, and the debug levels — for leaderboard 1.0, 2.0 or 2.1. Preflights the whole stack (version pairing, maps, ports, agent class, sensor budget) before spending hours, and hands the world back in async mode. Use when the user asks to "run the leaderboard", "evaluate my agent", "run routes_training", "resume an evaluation", or "reproduce my submission locally".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.